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0o Report ETL-TR-72-6

"4J , ,A MATRIX'EVALUATION OF REMOTEI>' SENSOR CAPABILITIES FOR MINLiTARY

GEOGRAPHIC INFORMATION (MGI)

byT. C. Voge,M. J. LynchA. 0. Lind

"- oc R. W. Birnie

July 1972

0/•/ Approved for publa redease; didrihbtion unlimited.

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ID DC

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NATIONAL TECHNICALINFORMATION SERVICE

0U S Nprto of C,ý.,sNP"ýQfl-ld VA 22131

U.S. ARMY ENGINEER TOPOGRAPHIC LDORATrORES

FORT BELVOIR, VIRGINIA

BestAvai~lable

Copy

Secuiaty aauaftfcatlen

0 DOCCUMENT CONTROL DATA.-R & DIYd(Stc-Ofir CISSSalllcagln of title. bndp of abstract and in~dexing swr~oban~ musta 6. entand When site oo.,.Ih_,ý,8fe4aII

I. OAIGINAYING ACTIVITY (Corpmfe, outhwr) ZO. RPORT1SECURITY CLASSIM"AlAION jUs S. Army Engineer Topographic Laboratories U'~fe

FotBclvoir, Virginia 22060 2.ýnu

3. REPORT TITLE

A MATRIX EVALUATION~OF REMOTE SENSOR CAPAlBiLITJ~sS FOR MILITARY GEOGRA.PHICINFORMATION (MGI)

4. OffICRIPTIVIE NOTES r-7 off" aeo~nd Inetuiuev dateip)

Technical Report_______S. AUTHORIS) CFif fflae. 81109 WrerIita laft name)

Theodore C. Vogel AnWi 0. LindMathew J. Lynch Richard TY. Birnic

6- HZPQRT OATE IT,&, TOTAL NP. OPPN PA07s_ -1ýJtly 1972 = __________

C'ONTRACT ON GRANT NO. 90. ORIGINAT:RS ;EPORT NUNRIERISI

It. PROJEC T No. 4A062112AC54 TTR7-

I a. S1b, OTHER REKPORT NOMS (Anj oil,.,fu abe,. UMatAi b~e 6. latpedI this report)

> ~10. OISTIUBUTION STATEMENHT

~Approved for public release; distribution tm1~mited.

I .$P1L.E&ENTARV NOTIES 113. SPONSORING MILITARY ACT. fTV

110 J. S. Army Erigincecr Topograo~iie Laboratories0j Fort Bclvreir, Virghira 22060

is. ABSTRACT

l1ids work 6~ an initial a ttenopt to ce..V.,atc 20 wlekded rem~t-' twiphur types fur tlxi, abiliq to obtaindata on bpecifit natural and culitural torrain cumpuntnta (81 twledt. d MAG! clement.) r.:~ Ialh~tUIO 1r ertmade at titst c lcvo,6 according to the cumple~xit) uf flit, MCI element and the Inetidf e,.perii~ncc requirudfrom the interpreter. Thc MG1 cemLca.,t w~rer wegstcrisd ifltu futit major ditimuiu:. (1) Dratinage asid ~1.att 1,(2) Vegetation. (3) Landrforms and Surficial MatrriaL,, and (4) Cultural and lnutilLuimc.Tht

'2 problemes as~tu4I] stdith deteetivun f ewdi NMGI cltmt 'it. rv~unlntsndeldu 111'erpladativis -dniquu ,,aiwd thtK'' referenct-s pertinent to each evaluatiorn ur prc.ented.

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VAAte iH..ty Cl..asszuiclUon

KIY WORDS LINK A LINK a LINK C

________ os~w W? 'ROLIZ T . F OLC 3?

Remote SermirgEnvironmental AnalysisTerrain AnalysigMultiband Photography"Aerial PhotographyColor PhotogrAphyAerial Camera,lilitaty Geography Informution

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U. S. ARMY ENGINEER TOPOGRAHIC LABORATORIES

FORT DEL VOIR, VIRGINIA

° /" Report ETL-TR-72-6

A MATRIX EVALUATION OF REMOTE

S/• SENSOR CAPABILITIES FOR MILITARYGEOGRAPHIC INFORMATION (MGI)

July 1972

',

Distributed by

"The Commanding Officer" U. S. Army Engineer Topographic Laboratorcfs

N Prepared by

T. C. VogelNI. J. Lynch"A. 0. Lind-R. W. Birnic

Photographic Interpretation Research DivisionC ;Geographic Sciences Laboratory

A ppro% ed for publi,- dI,- ribution unlimitt d.

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SUROIIARY

L- !• This work is an initial attempt to evaluate 20 selected remote son ,r ty•pes fortheir ability to obtain data about rpecific natural ati cultural trerain cumpolwnts (81'selected MGI elements). The evaiuations were nm;de at three le.,els according to ,hecomplexity of the MGI element and tie level of experience required from tie inter-"preter. The MGI elements were categorized into four major cdivisions: (1) Drainageand Water, (2) Vegeltation, (3) Landforms and Surficial Materials, and (4) Cultural an.Industrial-Economics. The problems associated with detection of cach MGI ele•ent.,recomnmended ý..tcrpretation techniqtcs, and the references pertinent to each cwtiua.tion are presented.

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FOREWORD

1. Authority:

This report presents a first iteration of a sy.'ematic analysis of sensor cwoabilitiesto acquire data base information. The work was performed by the Photo Int~rprCta-tion Research Division (PIRD), formerly of the U. S. Army Cold Region5 Rt-sei-hA itndEngineering Laboratory in support of the USA ETL Military Geographic Inforwatz"n, Program utder an intra.Army order for reimbursable services. Authority and guidancefor establlhhmcnt of this Work Unit is thc letter of 11 July 1968 (Dr. K. R. Kothc,Chief, Geographic Sciences Division, USAETL, to Mr. R. E. Fiost, Chief, Photo Inter-pretatio, Research Division (PIR D), U SACRREL) subject, "Trrain Data Require-iments- Sensor Capabilities Matrices," and a subsequent letter dted 26 February 1969(Mr. F.. E. Frost to Dr. K. R. Kothe) subject, "A Matrix Evaluation of Remote SensorCapabilities for Military Geographic Information." With the subsequent transfer of

••/ PIRD to USAETL on 1 September 1970, the work was completed inhouse by that> element.

,. Results:

An Interim Report, dated December 1969, was submitted outlining the methodsand procedures of this study. This final report expands the initial report end presents.%the results of the evaluation of remote sensor imagery (R.S.I.) for military geographicinformation.

This report is considered to fulfill the initial rcqui~remcnt. Subsequent teting ofsensors and sensor output to edblail'ah th,;*. A ' ie required-.................... ., tu pio uu c L c cq ird at -b s

"elements of information will lead to improved iteatiurb of the matrix in e.sentially theminie format. The results of this first effort, therefore, are a basis for elaboration andclarification as experimental evidence accumulatet, from the controlled tetsis and analy.ses which will proceed under other work units.

The reader shotil b,- .,ware that a conscious polio) ha., been followed in decidingmatrix conteint; i.e., the more inclusive claim of capabilit. ha-, been accepted in :llmarginal cas-es where a clrar.t tt decision %as not emident. Thi, stratep, it is anticipated,vwill evoke readier response which is eagerl% sougl.t to impru% v the matrix with construc-ti'e criticism.

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3. Format:

Tile reader ,hould not proceed to examine the matrices directly because they willscem miskiadii.g and complex ivhout prior knowledge of the sy mboio6y, inethodo! igy,and ration•iw for their corstrudion and, especially, the bas, for the decisions and the.reservatir,ns which accompany them. The mtrikes can be rtad simultancousdy witheach dAta element explaratlon. The bil ographie references are keyed to permit asso-ciation with particulai decisions. An orderly reading as suggested will lead to faster"comprehension.

4. Acknowledgments:

The final report is the result of a joint effort by several people. A. Lind (prea4ntl)with tlh Univzrsity of Vermont) and T. Vogel designed the original Matrix format andthe ;,umerical schetme used in the evaluations, Lind was also responsible for Cte sectionou, cultural dements. T. Vogel con.piled the section on vegetation, M. Lyr•ch the sec.tion on landforms and surficial materials, and R. Birnic (presently in gri.duate school,llHa:vard University) was ;nitially responsible for the section on liydrcoogic elcments.This last section was subsequently revised by Lynch.

K,•. The authors would like to express their appreciation to Marvin Gast, Chief of theGeographic Application Branch of the Geographic Scienes Division who tupplied dtelisting of MGI elements and Donald Orr of the Techno!og Developmcnt Bratach whioact•.d as study monitor.

"The authors would also like to acknowledge the other memhers of the P!RD fortheir ihdplul suggestions aid di,'uss~iun, in particular Dr. Jack Rinker, Robert Leighty,and Ambrose Poulin. Interaction in the final stages with pirmonnel of the sponsoring0. Geographic Information Systems Divition helped greatly to sharpen the prescntation.

The worl, for this report was performed tinder the general supervision of R. E.Frost (Chief), Photographic Interpretation Rcsearch Division.

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CONTENTS

"Sction Title Page

6, SUMMARY ii

FOREWORD iii

TABLES ,i

I "INTRODUCTION

1. Purpose 12. Scope 1

SII PROCEDURE

3. Military Geographic Information Elements 1a. Drainage and Hydrology Elements (100) 2b. Vegetation Elements (200) 2c. Landforms and Surficial Materials Elements t300) 2d. Cultural and Industrial-Economib Elements (400) 2

4. Remote Sensors 25. Image Interpreter Capability 46. Sensor Ranking 6"7. Matrix Format 68. Explanatory Notes 69. Explanatory Notes for Hydrologic Elements (100 Series) 7

a. Evaluation of the 100 Series 7ib. References and Bibliography for the 100 Series 40

10. Explanatory Notew for Vegetation Elements "130 Series) 60a. Evaluation of the 200 Series 60b. References and Bibliography for the 200 Series 73

11. Explanatory N otes for Landforms and Surficial MaterialsElements (300 Series) 84

a. Evaluation of the 300 Series 84b. References and Bibliography for the 300 Series 116

12. Explanatory Notes for Cultural Elements (40G Series) 133a. Eialuation of the 4uo Series 133b. References and Bibliography for the 400 Series 141

III I)ISC'USSION

" 13. (;eieril 146

IV CONCII'SIONS

14. (Conhluiorit 148

TABLES

it

Table Title PFge

* I Selected Airborne Remote Sensing System Types 3

II Matrint - Drainage and Water Elements 59

III Matrix - Vegetation Elements 82-83

IV Matrix - Landforms and Surficial Materials Elements 132

0 • V Matrix - Cultural and Indurrial-Economic Elements 145

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A MATRIX EVALUATION OF REMOTESENSOR.CAPABILITIjS FOR MILITARY

• "GEOGRAPHIC INFORMATION (MGI)

I. INTRODUCTION

1. Purpose. This rport provid.sa, more 4uantitative method of e, aluating thecapabilities of remote sensors with respect to a selccted list of Military'Geographic Information (MGI)l elements at two levels of iwr ge i.,terpreter training aad experience(c.,sentially novice versus experienced interprct,.r). This stualy is in suppuit of advancedscnsor configuration and performance requirements.

2., Scope. The evaluations are based on the U. S. Army MGI requirements-asdeveloped in an experimental data base by USAETL Geographic Information SystemsDivision. The primary source of information nccessary for evaluation of the bensor/MG Icapabilities slccted for this study was scientific and industrial literature. Actual cormparative anal)sis and clvhu.ttion, of remote sensor test imagery, and data wvere precludedfrom this initial phase of the stud) because df the difficulty and fiimc involved in collect."ing rcpresentative arnaples for each remote sensir. The information gained from review

Sov of the literature %v as tempercd with t!ie experience and background of projct personnelbefore each evaluation was made. In gencral, an objective or quantitative technique forevaluation of remote sensor systems does not now exist.

In cases of doubt, the more inclusive claim for a eensor capability was made

igp ordcr to evoke reader interaction. Thist does not entail, lavish claims based, for exam.pfIc, on one cited atse but doe include marginal but credible claims which could not bercsolvcd. Both experimentation and reader interaction will be depended on to achieveia r•fined iteration at a later date. A controlled photographic imagery anal)ysis program"is already under way to provide the future improved data._V

II. PROCEDURE

to 3. Military Geographic Information Elements. This stud. is largely an attemuti" to li.•hd tltt' initial %vorking method fur a (-otimlitig program in ,upport of thc MG Idata Lasr and datal hank program currentl) under development by USAETL. The pre''-

"•. . enit list as, rct ent!v formulated k USAETuI. numbers -vell over 5,000 chlments. Applroxi-:inatshl 2 percent of thes' clem|ents are conssidtred lhre.

~I( \!,1 -ddm f i h. .t)o g cg'~.ipstpluaI I[actor., bot cu~turaI and n.•turad IIbt ,4frcI ,a mribLr -tua t . flu.o)

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Various ckhs-Iifcatior. sch~emes may be applicable to the wile va~iety of__ ~natural and man-mutde features of the terrain. In this study, four m;.Jor categories -Af

dat4 elements are identified and coded as follows: (1) Drainiage and Hydrology Data(100 Series); (2) 'Yegetation Data (200 Series); (3) Landforms and .3pUficial MaterialsData (300 SerxE); and (4) Cultural and Industrial-E conomiic Data (400 Serieb). Whilefurther divi'.ýori may Le mnade, depending on the specialty prefer--rce, involved or thenature of specific problem areas, ihe fourfold division used her,. dorus not differ greatlyisomn ax~epted topographic data .:oncepts already in use by the U. S. Army. Overl~ipbetween certain major categories of topobgraphic, information seems inevitable; how.ever, It is not the categorization or classification of the data that is to be stre&-ed but

ratfer the discrete data elements thembelves wvhich aue of primoc importance. Whlk thetilles of the above major categoriets are self-explanatory,, omrnf clarification is in orderto indicate areas of overlap.

a. Drainage and Hydrology Elements.(10'J). Included in this category arethe characteristics- of water bodies, ,uch as streams and lakes, and those topographlicelements which arc intimately associated with these features. Thu-6, river bankt andshorelines are considered here rather than uznder surficial materials and landforms. Afew man-made (cultural) features, such as reservoirs, canals, and drainage ditchee, aiealso considered under this category.

b. Vegetation Elements (200). All vegetative compon~ents are included inthis category whether they art composed of man-made or natural elementb. Althoughcrops are of cultural and economic importance. they are also vegretation or botanicalelements from the imiage intcrpreter't, viewpoint, and the methods of deriving crop

possible exception of image scale.

C. Landforms and Surficial Materials Elements (300). JBedroC!., overburde~n,and landforin elements ire grouped under thiL. heading bec.-mbe tLey are closely relatedand, from anl image interp~reter's standpoint, virtually insepirable.

d. Cultural and Industrial.Economnic Elements (4Wh). This categor) inclmuccsthose man-madle features of the terrain that re~sult fromt h':man ov-cupant nu~t coveredin the other categorie-s. hinluided *ire such diier.-w elenentsas, ruads,, railroads, buildings,indunstries, and land use.

4. Remote Sensors. Thel selected li~st of e~irbormi remnote sesn ysci n!por-tions of the elec tromiagnetic :sprlruni ewasidered inl this.study are presenlted int Table 1.Inl searching for a metthod to dk ide-fi the t troinaitigtir spectrum inituo orkable unit.', itbecamec e~idt-nt that ti% o awnue.s of approat hi %crv topt-n. (1) di~ iding the spec trtani intogeneral uni6mt, i.e., rad'ar, inicrowame, etc.: or (2) listing individual. zv:.nor.,. ixe., APQ(57.

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0

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K-17, etc. Both of these methods have sewre ii.nitations-the first because of the gein.eral disagreement ,n limits and the overlap that exists in the major Jivisions of the dec-tromagnetic spe,:trum, and the second tr.causc it wouzld produce a,t exceedingly longlist of rerntmc e.nsor hardware, The list finall) adopted for this study considors 20 major sensing systems (designated by capital letters in the matrices) and probably shouldbe considered a combination of the above. These major systems represent a ,,rge num-her of individtual remote sensors. As an example, a 25A filter used in coniunctiozl with

O •panchromatic film would be evaluatcd under the "Panchromatic photograph)" category(B, Table I) and referenced under the pertinent MGI/scnsor evaluation.

It is assumed in this study that all remote sensor imagery and data is of thehighest quality obtained at recommended exposures, gait" settings, etc. For instance,vei tical photography would have been obtained with less than 3 degrees of tilt. It is alsoassum.:d that fo, those MGI elements r.quiring photogranmmctrk measurements bothvertital and horizontal ground control is a&ailablc, and imagery tcctification is possible.

Theve matrices emphasize the present major sources of NIGI, i.e., panehromat-ic and .;olor photog.aphy. It is of importanu to note that this emphai, ib should not de-tract from the impouranct: of the other sensort, but, rather, reflects thle long histor) anddevelopment of ae|'al photogra ,y s a tool for gathering terrain information.

5. Image Interpreter Capability. The It-t of remote sensors (Table 1) should be1 onsidered as remote semor ,ystems rather than individnal pieces of hardu are or portions of tile electromagnetic spectium. The airt raft pilot, photogntpher, darkroom tech"nician, and the image interpreter are also part of tile systen,, and, if an) one of these

SSholluhi fail, thenl, of course, teio entire ysten fails. This sud)i a'temp., to calhatc twowhnponents. (1) fle image int,-rpreter, and (2) the r motie senor. The remaining com-ponlents, while important and which should aLo be -%aluated, ,ic no t ontidcred to be

( '. within the scope of this study.

The ability of tile lmtep•nr.mer Ic Jeternhne individmial MGI data elements hasbeen di'.ided into two leve,. (a) the interpreter w Ito ha.- Lwit knoi ledge, a& proidedby militar) image interpretation schools, but IV Ith dOc. nut lieo t xteni.,ie experit neeor training in tht terrain and enginee'ing s•ciCnfc, , tict rued %vith M;IL. and (b)the cx-lx'rhivived interpreter who has the complete bre~nlah of requirtd t clmii al kmowlct!gbuth in tOw terrain and engineering ,,ok.no, it. iminqwc-inte pretation .-kill.-. Lt thiet,body of the ma'rix, these leveL' ire coded aw.:

• •.0 1)robzble failhre at both levels of interpreter (xperiem(T4

(extenssive ground data olhlection ot -,uppl- meivn!ar* .wsen..,,r imagery or data i6 gencral.N required at the pre.sent

" "'• ,~tate-..df.the.,rt ).

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1 success probable at Nigher exnerience level only.

2= success probable at both experience levels (successle* •' at this lower level cannot occur without success at

the higher levcl also).

X = remote sensor-MGI elen Cer combination mutuallyexclusive or incompatible.

Selection of an appropriate entry in the evaluation cndc (O,1,2,X) was basedon the experience of the authors" capabilities, the literature they review ed, and thecomments of colleagues.

These evaluation , ides signify that, generally, in the authors' opinion, the in-dicated level of interpreter ex perecnce is the minimum needed to extract the MG! ele.mrnt ftom the imiagery. The nodifying statement "generally" is important because inany entry there %vill be except ,is, and there w•l he instances where a supposedly diffi-cult M.•1 requirement cc-i be a ;complished by a less experienced interpreter, for exam-ple, extensive use of imagc intec pretatiun key maps or other information for a particu'oNMGI element by a teehnician-leel interpreter (code 2). In all entries where success isindicated on both high and low lvels 4f interpreter experience (code 2), it is assumedthat the MGI clement is well defihed and easily identifiable. In those instancv,-, whereonly obscure trace.- or other subdt and indirect Lidence exist, the services of a skilledinterpreter are required (code 1).

a. -° The entry "0" is eottstrticd to mean tdal at the pre-,sent state.of.tlhe-art exten-rive ground dala or suppknimcdary ot conipiex inferred information is required to obtain data on this particular MGI elemitit.

"The 'X" entry is defined as a. incompatibility of the remote senswr- MGIelement selection. As examplis, a gravineter could not be utilized to determine uoil orvegetation color nor would a laser profi;t'i be cmploy,,d to determine tiw area tf a fur-est Clearing.

Other than the mutuall, excluh.ive ntrivs (code X), no 'llohancci ha., been"made for the appropriatcmesns of each st•Lor-cl,-nent match. Entrie.s ha't been madewhcrc,-r it is at least theurcti•all) po.-Aibl to tl,driic useful data, although it i.s ret og,nlzed that tIle partiu!'as .'en'sol may not be pratt, al!y us. d for that partit ular purpo.t

j It iV at..unmed that this matri-. % ill enable rational ti tcrinuatitn, ,if ,.e-Air v-let tiom andSxi.'t-ted interpreter INxrformance.

6. Sensor Ranking. An attempt was made to aelect the three most generallyusefOl sensors for obtaining information on each particular MGI element. A code(AB,C) was used to indicate the selected sensors and to rank them ("A" indicates firstchoice). Criteria used in making the selection were the inherent :.. rmation contentof the sensor imagery and the ease of detection and interpretation. In some instances,an identical double entry was made where it was difficult to decide which sensor was"most su•.able. Two sensors, for instance, night both be given "C" ratings (third-choicerating).

It was assumed that these sensors would be operated under optimum, day.fight conditions. Suid an assumption neccs&,arily puts bias into th,. selth..•n and doesSnot give due consideration to such ensors as radar which can operate at night or can

v image through cloud cover. A more complex code which could moric realistically ac-! commodate the broad spectrum of remote sensors and include environmental consider-F 1ations could be formulated in the future.

7. Matrix Format. The MGI elements presented in the matrices are numberedin such a manner that the number idcntifiti the category to which the element belongs.For example, 101 is the first data clement under the Drainage and Water category; 201would be the first data element under the V%.getation category. As more ý-.lemcnts areadded, the element numbers can be increased to four digits, ýhus allowing for an open-eaded MGI element list. The elements arc presented along the left margin oi the mv-trix with the sensor systems formi~ig the top of the matrix as c:dlumns (Tables 11 itroughV). (The tables are located at the end of paras. 9, 10, 11, and 12.) The evaluations ofthe sensor systems and sensor ranking for each MGI clement are located at the intersec-tions of the rows and columns. As ma) be expected in a study of this type, ijumerousexplanatory votes are necessary to provide the limitations and auxiliary infoi mationfor each MGI element sensor evaluation.

8. Explanatory Notes. Paragraphs 9 thirough 12 provide the reader with thedetails and problems asso~ciated with the detection, identification, interpretation, ormeasurement of each MGI element. Each element is defined. The interpretation meth-

r° ° ods are discuaed, and recommendations are presented for the most suitable remoteb sensor. The references and bibliography ror the evaluations ran be found at the end of

each of th.- four categories and are keyed to each M(;I element by their matrix number.

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9. Explanatory Notes for Hydrologic Elements (100 Series).

a. Ev~duation of the 100 Series.

101. DEPTH OF WATER BODY

(a) Definition: A determination of the vertical distancc from the water-airinterface to the water-bottom intcrface.

.> (b) Interpretation Variables: Because of tile nature of water, most proventechniques for remotely determining water depths have been restricted to the photo.

K graphic systems. There are three main photographic tec'muques for determining waterK, odepths (Sont, 1964):

(1) Penetration Method: Imaging of bottom of water body; light energyhas penetrated water and has been reflected from bottom surface.

(2) Wave Method: Analysis of the shoaling characteristics of waves ap-proaching shore; depth is inferred from wave transformation behavior.

(3) Transparency Method: Analysis of tones on photographic imagery;depth of water is indicated by extinction values of light emerging from the water asportrayed in photographic tonal differences.

Photographic penetration techniques have proven to be the most usefuland accurate. Depths of penetration and imaging of bottom detail as reported in theliterature have ranged frow• a few feet to about 150 feet; the greatest depths tend tobe in tropical ocean watei. Imaging of bottom surfaces depends on the contrast of thebotten as well as penetration of light.

Photographic techniques (other techniques also) for waterdepth determi.-"nations are complicated by the fact that, in addition to problems of light transminisionthrough the atmosphere, there arc the problem., of light transmission through a water

K medium. Water quality it the main factor controlling the depth of penetration o; light.A good dicu-•sion of the basis of thits problem is presented in the Manual of Pho.o.graphic Interpretation (1960), Chapter Two, Appendix C: "The Procurement of AerialPhotography of Underv ater Object,- An Analy.,si of the Problem by Russia Scivntit'ts."

(c) Remote Sens, - Applications: \\ ater depth,, can ib determined by r,.,ing a. ancty of photographic cr meiions that record i,.flcutcd light from bottom surface.:. ofwaier bodie.,. Color film, ippeir to be the most widel. ut.d for depth determinations((;'ary, 1968; Var), 1961;; Schueider, 1968; Suan-son, 1960, 1964) Techniques

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range from estimates to photogrammetric methods. Depth determinatio;ý,s from stcreomethods have had accuracies of ±.5 foot to depthof 10 feet; this accuracy was valid"fdr altitudes between 1,000 and 10,000 feet (Conrad, et aL, 1968).,4 •A method of depth determination using a stereo plotter and vertical pan-chromatic photography was initially described by Tewinkel (1963). This method asmodified by van Wijk has achieved an accuracy of 14% for moderate depths. Joering(1969) has alhu used panchromatic vertical airphotos at a scale of 1/6400 to estimatestream depths with good results.

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Multispectral camera teehniques should have good potential for water-dtptli determinations since it is possible to select those wavelength bands of light raxost

L transparent to the type of water being investigatcd. Maximum and minimum values ofabsorption and scattering for various wavelengths of light differ greatly between river,lake, and ocean water. A number of articles give the depths r:cordcd with variousfilm/filter combinations on various types of water. (Some of these articles arc listed as

I references at the end of this presentation.)

Laser ranging sensors have been used to measure depths directly to 150feet from an altitude of 1,5011 feet (Polcyn and Sattinger, 1969). Air-droppable pene-trometers may also be able to provide point data on water depth.

Estimates of water depth are also possible from Apollo mid Gemini type•: imagery (Geary, 1968).

iarY( Depths of y )mall mountain lakes have been determined rathlir accurately

b) a technique based on measurcment of shuic slope's from photography (Muc.sner,1963). It may also be possibl- to apply similar techniquet to some riverts and streamni.Determinations of the depth of small fakes, streams, and rivers can aLo be aided b) anumber of natural and artificial featureb that give clues to the water depth, somne of

these features are boulders, rapid.,, and riffle.s, tree stumps in flooded area-, t) pt : ofaquatic vegetation; buoys; fords; and variou, long::hore cultural features.

" epth changes can also be inferred using a standard hydraulic velocity andflow formula if veloit. changes acr-., a str.anin crots .-ection can be determined.

102. VELOCITY OF WATER FLOW

(a) Definition: A determination of the rate at shlih surface water i6 flowingin a stream or other water budy.

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(b) hlterpretation Variables: Various techniques have been employed for"etermining the rate of surface.water movemcnt in streama, rivers, lakes, and oceans.SThese techniques have ranged from simple estimates of flow velocity to complex photo-graznmetric procedures. One common problem is locating reference points on the watersurface. Various natural features and artificial targets have been employed as reference

points including waves, eddies, lines of foam, zones of discolored water, floating ice,floating logs, and steel drums.

Among the methods used for flow-velocity determinations, techniquesutilizing photography have been the most common. A variety of cameras, lenses, films,and image scales have been employed. In general, larger scale imagery is needed formaking flow velocit determinations on streams and rivers than on large lakes and oceanareas. Very small scale photograph) has been uted successfully for determining veloci-ties of occa:, and tidal currents, and TIROS-type imager) has been used for monitoringmovements of large ice packs.

(c) Remote Sensor Applications: By measuring the movement of converginghines of foam, dkvolored iu ater, and floating targets with timed, sequential panehromat-"ic photographs (scale 1.80,000), Keller (1963) determined tidal current velocities with-in a ±2.knot accuracy. Other studies usin. floating targets have been described byDuxbury (1967) and Oros (1952) for thl- Cohmbia River.

Photographic parallax methods have been applied to the determination ofcurrent velocities in streams, risers, lakest, and oceans. Forrester and Cross (1960) haveused panchromatic photograph-. taken at altitude.s betueen 3,000 and 6,000 feet to ob-lain photogranwictric measurements of stream flow that are within 10%, of the valuesobtained with standard stream gauges.

Cameron (1962) states that with scales ranging from 1:6,000 to 1:60,000it has been possible to determine water velocities ranging from 0.25 to 14 miles perhour. lie also states that the main factor, limiting vebcit, drterminatiois are theamount of water displacement during the time interval bet ueen succes.,sive photoframes and the (photo scale. A wide latitude of water-*elocit. differences, however,canl be accommodated when obtaining avi ial photograph. b.) 'ar ing aircraft speed,10photo scale, and time between photo frames,. For verN iou current velocitie.,, it ma%even be i es.,ary to make a succesive run. (,,anron (1962) also gi0 es d(ftails, for rer-ognizing and Cori'eetirng for anonialoa,| surface-% ater mo' t-nients caused b.) wind.

El.Stimates of ý.urta, e-water ,velocity haw, been made based on obmer'ationof %vas'v pattern,, on low lvcrl lhotograiph. (Polch. n and S..ttingrr. 1969; Paulson, l06B).Krudrist-kii, e1 al. (1956). has estimated strea ih(lo ( h• itiv's from arial lhotogaph:(1 :3,000 srah.) If% an:al'v ,inz 11it uake, proldut rd b1 ol.irutt liown. J16ring (1969) used

&P

panchromatic photographs at a scale of 1.6400 to estimate stream-flow velocities. Ob-struction wakes and other wave turbulence effects have been observed on radars of bothpoor and excellent resolution.

Radar returns from artificial reflectors have been used to measure ocean.current velocities (Nikiten, 1957). Similar techniques may also work with naturalfloating reflectors such as ice floes. Low velocities are detectable with Moving Target

Indicator (MTI) radars.

Radioactive tracers have been added to water and monitored with gamma-ray spectrometers to determine velocities (Zoitzeff and Sherman, 1968). In a similarmanner, chemical dyes have been used in conjunction with sequential photography.

Observations on the rate and magniitude of movement of ice packs have0 been made on Apollo type imagery (Cameron, 1962).

103. BANK/SHORE LOCATI')N

(a) Definition: A determination of tlc position of the air/water/land interface.

(b) Interpretation Variables: To determine the location of the bank or shoreand water interface remotely, a sensor must be able to discriminate between the waterand the land surface. This is generally pussible since water and land differ in character.i •s~ties of reflectivity, thermal proper tiecs, anld topographic expression. Boundary determi-

nations are ustially easier to locate where tlerc is sonic sharp topographic break at theland/water int.:rface. This boundary can be obscured by aquatic and land vegetation

S~especial..) in streams and ponds. (See also cats-gory 108, "Area of Flooding.")

(c) Remote Sensor Applications: Aerial photography has been widely usedfor location of bank and shore ho undarie-s. Verti ýal photographb are most commonly

0 used, but other formats such as oblique are also utful. Scales vary with size of waterbody, nature of land/water interface, t) pe of film, and accuracy requirements; but,generally, larger scales are needed for accurate boundary determinations on istreamb andponds than on larger water bodies. Stereo coverage ii generally neccsary for high accu-racy. General drainage maps can I c made from aerial photograph) of very small bcale.

For drainage mapping at a 1/20,000 seal which includes tertiary-orderstreams, Anson (1l66) has dhown that detection abilit. insreaýe. from panehromatic tocolor to Ektad.-ome Infrared photographic cmulsiun•s. Infrared film i, tsuperior to nor-Mal photograhii, mulsion.s bcau•e of the high rellectivit) of vegetation and high ab-sorptanuc of w itt' in the nmar-infiared amclength., Land,'water contrast is enhancedand egetation arf -. arc highlighted. The ubefulnch , of infrared emultions for drainage

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studies has' .ýxtensivcly documented (Coviwdll, 1966; Jones, 195 7; Lohman andRobinove, 1964; Marshall, 1968; McBeth, 1956; Robinove, 1968; Ross, 1969;

ýN Schneider, 1968; Swanson, 1960, 1964). These studies a~so show that color IR per.mits tracing of the drainage closer to its source.

Black and white vertical airphotos at a scale of 1:24,000 huave bcer, used /succes~fully to locate drainiage ditchecs (Sternberg, 19G1). Imagery from a multibandcamera system (nineti lens) at a scale of 1 ý2O,000 has been uwed to locate pond's andrivers and their bank boundaries (INMolineux, 1965). Some work has beeni done %'rtliwaveform ai5alysi.3 of multisensor imagcry whereby drainage channels arc automaticallylocated according to gray-totie signatures (Latham and Witmer, 1967).

Thermal infrared, and passive microwa~ve imagery can be used to locateland/watur boundaries. Differ-ences, in thermal properties of water aiid materials !'',nup the land surface provide the basis for discrimination. Spatial resoluliori. of the i.nag-cry , however, is poorer than photography especially for passive inicroiwavc iniage'y.

Radar imagery, cipecially sidc-looking airborne radar (SLAR), ca.a be I..edzq" to map drainage on a bmall..sutic, wvide area hbais. Drainiage channels can be ,utliincd in

stark detail depeniding on the amoutnt of local channel relief, resolution of .adar equip-ment, and orienitation of channels wvith respect to the radar platform. It. Aar has thecapability (real and apparent) of penetfiting vegetation to at certain dey' rec and can beused under a variety of atmospheric conditions during the day or nigAt. Witter areas

'~ rwivll genecrally show up on radar imager) as, "no return" areas beeso x of hligh specula,reflection (for smooth surface.) of incident radar energy. If the l..nd surfacc along theedge of a waiter lbody exhibits sufficient relief or niugluines, esp'cially at the usuallyshallow angles of incidence, then the initerface should 1w rz.dd;y detectable. Small-scale and lirnitci resolutiota, htowever, affec(t the overall accixacy of land/water inter.face determiniations.

Radar imagery is especially useful for bovadary mapping of large waterbodies. Very -,mall wvater bodieb, how ever, may go vadeteeted. InI a general stt dN ,Simpson (1969) reported that ponids oni the order ,,f 200 yards in diameter were on the

Ntý I threshould of deteitability on the radat imnagery eAarnhed (15 mile-wide strip imageryA PQ-97, K band).

Laser terrain profilerts have the potential to accurately determine 1sater/land bounidaries oni the uai f relief and surfaye rutighnetb. TIhe lbser provides on~ly anarrou traue, hovw cc and does, wit have the bioad area civerage that imager) pio.vides. Therc also tan be proble 'Ins with deturma~iinig thu exact geographic location ofthe laser trate, anid atiunnalouti return signals caii be generated. Link (1969) reportedthat at laser profiler (opt-ratinig at 63213A) tiovv i at an Ititude of 500 feet at a speedj of

Ow

; :• i250 feet/second had a vertical resolution of 0.3 fooL and a horizontal resolution of 1.,feet. The laser can be effective, however, if flown with a boresight camera with sufh-cierit care.

104. BANK/SHORE COMPOSITION

(a) Definition: A determination of the composition of the materials compris-t ing the bank or shore of a water body.

(b) Interpretation Variables: Numerous techniques and clues are used to deter.mine the physical apd chemical makeup of bank and shore materials. Esscntiall), thesetechniques are simar to those used for determining the composition of surface depositsand mat.rials in general. These subjects are discussed more thoroughly t;nder elements301 (Type of Surficial Deposit) and 302 (Composition of Surficial Dcp.s;t). Otherpertinent eiuincnt; are 109 (Stream Bed Composition) and 107 (Bank/Shore Stability).

0i

y Of particular importance to the determinaton of bank/shore composition,other than spectral reflectan.e characteristics, arc evaluations of the -hapc and featuresof the bank or shore such as gullies, cuts and vegetation, and the general stability andbehavior of bank/shore materials in relation to %arious ,ctive hydio-processes of asso-ciated water bodies.

(c) Remote Sensor Applications: Photograph), in general, and color and colorIR photography, in particular, would probably be the most useful type of remote sensorimagery for determining the composition, major features, and general charactcistics of

-,,•:batiks and shores.

, 105. BANK/SHORE SLOPE

(a) Definition: A determination of the slope of a bank or shore surface asreferenced to the horizontal.

(b) Interpretation Variables: Bank/shore slope is a special facet of the overallproblem of d-....mining the slope of terrain features from remote sensor imager) which"is trea•.ed under element 314. Because of the generall) limited dimensions of most-b lsan'ks and shores, large ,calc imagcr) is ustuail nccesary for making the horizontal and%ertical mitasurements required for calculating slopets. ltepre.intatihce siteb must be selected and measurements madt along a tine from the land/wlater interface to the top ofthe bank or shore. Vegetation and cultural feature, can aid or hinder slope determina-tions. Other element- containing information pertinent to this discu"isi include 103(lank/Shor,: Location), 107 (Bank/Shore Stability), and 108 (Arca of Flooding).

12

J (c) Remote Sensor Applications- Stereo phot graphy, in general, would bethe most useful t)ype of remote sensor imag',ry for determining bank/shorc slope. Themost. useful film ty pc w ould depend onl the nature of the bank/shorc, ease of delineat-ing land/water boundarius and othur boundaries, and presence of v.egetation culturalfeatures, etc;. Color and color IRi films gencrally allow greater discrimination between

00 ~these various features6. However, oitler films, such as black and white IR, whichf is

valuable for delineating land/water boundaries, are useful.

Bank/sirore slope measurements of high accuracy can also be made by aAll laser profiler at selectevd cross section,3. Simulations, made at the U.S. Army Waterwvays

Exiperiment Station (WES) indicate that such laser applications would be effecti'eeven through dense canopy (draft of TERRAS report by A. Williamnson to B. Scheps,(USAETL), 1971).

~<106. BANK/SQHORE HEIGHT

(a) Definition: A detcrmi':tation of the eleiition of a banik or shore abovethe genteral water level.

(b) Interp~retation Variables: The determination of bank/shocre height fromt

remote sensor i 'nagery will not lie discussecl in detail here. The reader is referred totht. general discussion!, on clc~ation (313) indl slope (314). Thle determinaton of batik/shore height is a special catugory of the overAll problem of determining 0Liations of

4/ natural features. Since banks and shorets are gwnerally not of great magititude --erticalit' l1y, useful imager% for determining their height mutst neceessarily be of large scalc such

as L;3000. Land/iuater boundaries must Almo stand out clearly onl thle imagery. OtherJL4.categories in this report applicable to thr problem of determining bank/Ishore licibfit

include 103 (Bank/Shore Location), 10-4 (Bank/Shore Stability), and 108 (Area ofFlooding).

(~c) Remote Sensor Applications; Large-meale stereo photograph) isould gunCrAIdli e thle most u'eful IN lie of relfote sensor imtagery for determining thle height ofbanksb and shores. The Photography pro~idcs a contintious pictuic niap of the banik or

,hurt-, andl representative sitets tan: be: rvueted fur measuremtent. The lasert profiler taiiK0 c, promide highlN at-t ur~mte 4'ata on haink/shore height lbut ondN at seOet ted pointzs which

must k -iutn bt (ore or dluring tOe fitight PlisItm uhtogah -~tv~t irnliaIt

<*rut ortl of the bank/shore and permit.. lei-murt-1%i imrest igat ioi. and eleatkc nicamurt-nincatalong~an% part of the imaged baii. or shore. t olor and color lit film., uvould 1wt gvenr4111% More advanWtagous- for bankishaure lit ight dteterininiatioos tint v greater dim rmninatiout is usu11311 possible bruetv ci landI and uater, v-deationm, bank/shore mnaterial:., antlcultural features. Otht-r film.,. hou ever, van a~oproultive pod results.

107. BANK/SHORE STABILITY

(a) Definition: A determination of the permanency or resistance to change ofa bank - r shore to natural erosive agents.

(b) Interpretation Variables: The stability of stream banks a~id shorelines ofwater bodies depends on a number of factors ink 'uding the composition and size distri-bution of bank/shore materials, height, slope and structure of the bank/shore, presence

~ of stabilizing veguiation, and location arid degree of exposure of the tostrong water currents and wave;s. Banks and shores composed of resistant materialsmay be quite stable even when subjected to highly erosive hydro processes. Banks and

r~~. shores composed of eaily erodible materials may also be fairly stable if located ir. aIow-energy area tsuch as along a slow, meandering stream having a small yeardy dischargeamplitude; a quiet pond; or anl estuary backwater. Unstable bank/shore conditionsare brought about largely by a combination of factors such as -erosion -susceptible mate-rials and exposure to strong currenits s~nd wave attack due to storms and floods. Bank/shore failure or deformation such as clumping or landsliding call also occur locally

1;> through processes such as earth tremors which are not directly related to water-bodyerosion.

(c) Remote Sensor Applications: The identification of the type and composi.tion of materials making uip tht bank/,shore its an especially important factor for evaluat-

C> ing btability. Thes~e items are treated, generally, under elements 301 and 302 and, spe-cifically, under element 104 (Bank/Shore Compotition). Suich items as the shape ofetaw and gullies aid the interpreter in determining the general itature of bank/shore ma-terials. The presence of slumps and associaied f.atures indicative of failure also giftes,clues .,ýi to thle degree of bank/shore btability. Thle prcsence of manl-made, protectivefeitures such. as jetties and retaining walls canl alto be used in evaluating bank/shorestability.

One of thle best methods of determining bank/shore stability is actual ob.tservation over a period of time. S -cli anl empirical technique allows determination ofareas of change, rate of changc, and volume of material eroded or accreted and makespuossible predictions based onl obzterved treud,,. Bloth 4er*al and ground-based seqiuentialphotography (iiceluding motion pictures) have bcen uit idel usd for thi., piorpoc.

Zý Stafford and Longfelder (1971) repor't oti a coa-stal study in North Caro-1hi: in which sequential aerial photograph) i~as used to docunment change. Measureietats 1ueft i.,sadv at oelect referenci. point,, bt tv~ee the dune line ind high water linewith eou.iff~eration paid to the timte of year of the photograph-, and thle reprewentativeIest" of thle prevailing conditions. Rectifiedi enlargernivts protved try valuable, theiruse, rsulted ini the s.tuallest coipo.:-ik crior tof tht %arious hpes of photography

- I

employed. For a particular type of photography (rectified, unrctified, etc.), the com-posite error also' decreased with increasingscale.

"" Panchromatic film was used in the above study because it represented thephotography generally available from various government agencies. Color and color IRphotowraphy would also be useful for similar studies especiilly for identification of surface materials, associated vegetation, and cultural features. For large area surveys, how-ever, any added benefit from the use of color or color IR films would probably not out-weigh the additional cost.

The general literature on the application of aerial and ground photographyto coastal studies is reviewed by Stafford (1968).

Rea1.ote sensor imagery other than photography 6an also be useful for ap.'praising guncral bank ,and shorm conditionU, the usefulness dep,.ding largely on the scale,resolution, and quality of the particular type of intag,:ry. Pertinent information relatingto various types of remote sensor inagery is ýontained also :n element 103 (Bank/Shore

7 .Location).

In a study of the Delta River, Alaska (Digngman, et aL, 1971), a braidedglaia •stream, aeial and grouwd-babed equentitd photography'(pan(.hromatic) wereused to document short- and long-term changes in the channels and hanki, ,f the river.On such streams, the unconsolidated banks are particularly susceptible to erosion because of large diurnal and seasonal fluctuat~ons in discharge. Rapid shifting and migra

L ' • tion of stream channclsh Make the banks susceptible to erosion along any reach. Largescale photography on the order of 1. i0,000 or greater ib desirable for studying the bankconditions of such streams.

108. AREA OF FLOODING

(a) Definition. A determination of the area covered by an overflow of wateronto normally dry land.

" - w h(b) !ntorpretation Variables: The subject area of flooding has several facetsV which hiclude:

(1) Determining the area inundated during active floods.

(2) De.rrmining the area of recent floods from postflood survcys con-ducted within a mi;lativel) thort time after occurrence (for instance, 6 month.,).

15

(3) Determining the extent of older, historic floods. This category couldbe expanded to include ancient floods which properly belong i the field ofpaleohydrology.

j (4) Theoretically determining areas and depths of inundation for givenvolumes of water. Such calculations must be made for flood-control projccts and dams

° -• •and for general plarning purposes.

andforgeThis review of remote sensing techniqacs for determining the area of flood-ing will deal primarily with active floods and will be largely confined to the use of ierial"photography. Floods can occur on floodplains of streams and rivers and on low land"areas bordering major water bodies including the ocean. For example, hurricanes harvecaused extensive flooding of inland areas of the Gulf Coast.

Much of the miterial presentedl under dement 103 (Bzank/Shovc Location)

is applicable also "o the probtem of deterinining area of floods.

For making area determinations, some type of imagery is required. Usefulscales depend on the extent of flooding, contrast betwveen flooded area and surround-ings, type and quality of imagery, ease of boundary determirations, and accuracy re-quired. The geometry and mensuration quality of iar.ous typis of remote sensor imag-ery are discussed und,'r element 303 (Area of Surficial Deposit).

(c) Remote Sensor Application: Burgess (11967, 1971) gives a comprehensivetreatment of various photographic techniqaies fur conducting aerial surveys of activefloods. Both v -rtical and obliqza pI~otograph,) are useful. Photography should be obhtained at crest stage or j-ist prior to crest stage. The recording uf floods is sometime.,difficult because of the ne, essit) of planning missions on an emergency basis and &.cause of adverse weather conditions commo•h accompan. ing floods. Expedient pro-cedures must sofnietciS be used.

Large-format press cameras and lpanchromatic fimn have beet'. used to oh-'ain satisfactory oblique photographs of flods from lowv-,l) ing aircraft. Advert.,weather conditions can affect the quality of photography and limit the choire o( films.Panchromatic films are most cmmonly used because of their wide expo.sure latitude.

"e•° Color and color IR films can yield excellent data on flood-. if meteorological conditiow.s,1low their u,•e. Ilun" arnd Bird (. 9,) present ar excellent dbcui-,iunn on the optuum i

uSe" and limiting faauors (including meteorological factors) of 'aroil., types, of films.

Burgess (1967, 1971) also owtlines pro•edure., for conducting posbtflood• •survey's and re•iews the many dicrse line, of c'idenc,, that aran be used to de.erinine

: :•'-,16

the Limits of past flooids. Such deterrnination.% req'aire much skill on the part of

investigators.

Parker, et aL (1970), have utsed p,.nchroniatic and eolor photography to

determine tx(1967)agives af ghen1-eral rerrvtiew ofera floodpi deieton ai stemapingfouhrn pl cni.Te10yetfod sawdl sdidxfrWanning purposes.

and citian parametrs re ultspeuall dtelevisindsystmehasneerng sea toys obt~eain m

ery of flooled areas (Robinove and SI 'bitzkc, 1967d). Small-salie .3LAR imragery has

Thermal 111 imagery, as well as radar imlagery, wvoJd also have 1.aluc forconduct~ng surveys of active floods. Radar imagery, howe~cr, would be more app1rable for recording floods of wide areal extent.

109. !3TRFANI BED COMPOSITONle

(a) Definition: A dd.ermination of the type dud makeup of materials comn-prising the beds of btreama or other watcr bodies. -

(b) Intere-retation "ariables. Stream bed ctmpa6;.aon can refer to the gencralphysical t,- chemical mrakeup of bottom materials. Physi I~ makeup includes thle size:

-~gradations of bottom inatcrials, exprc.sse:d in terms~ such as sand and g~a~cl, and also thegeneral t) pus: of rocks and minc:al. comprisinig the bottom assemblagý. Chemnial cornposition can be inferced from the t) pe Identification of Lottom matcrials6. Thbis (.LCus-,ion applies not only to streams but also to the dct rminatior. of bottom materials inother water bodies as well.

tiori of surficial snat,-riic.l is disei-:,ccd under the suctioms onl Landfornis and Stirficial

ofsubaqueous, nuterials, hio~s '.r, an ;ater~t.iiumg w~itur layer of iary inc de~pth is presenitwihcomplicates tile use* of some s,,wsor.s andl nulibtie: thle ulse of others.

t~4

(c) Remote Sensor Applications: Various remote senso~rs can be used to de-f termine the cumposition of bottom mnateriais of strennms and water bodies. Both direct

and i:idirect techniques are usee,. lAi~ed~ techniques involvc the actual sensing of bottommiaterials by water peitetratio'i. et. . Indirect technique-s com. ist largely of interpretivejudgmetits made about bottum matt~rialo through an analyss of surfwe bank/shore ma.terialb, inaterials making up the watershed, etc.

The problem of determining water depth by remote means is discussedunder eloment 101. Much of this discii~sion ;s applicabic to the problem of determiningthe composition of bottom inaterials. ror streams and water bodies of moderate depth,Color plhotolpapliy would generally be the niost useful for determining bottom composi.tion. A skilled inteipreter is needed to make %alitijiudgments. Suich finctors as waterturbidity, however, limit the depth of penetration anid affect the overall utility of pho-tuaraphy. Many factors must be considered when plans arc made to acquire photogra.phy for such purposeb as dctermninizig depth of water and composition of bottom rnate-vials. Sonmc of these ncces--ary considerations are (liscumSed by Lukens (1968).

Mutch call be learned about the nature of streim-buttom materials by studly-

- ig the bedrock and surficial matecialb of the bttoaui watershed. These -all give clues to

t~te likely physical and chemical makeup of the btream-bottom materials. In like manl-vier, the maaterialts making uip the banks aid flouidplains of streams can be used as generalIndicators of t~le naturr of bottom materials (mce element 104, Batik/Shore Composition).

On water bodies other thapn streamis, much canl aiio be iiiferred about the

general nature of bottom material.. The bottom sed~mens of Lareas offshzore from deboucliingstreamnt and river, mutno likely wvill be, ,imilar to the sediments being dischargred.The sizr distribution of the bottomt s dimients will reflect the sorting action (if vario,.nearshore and offshn're currents withd sciliment size generaIl) decremring outward fromthe shore.

The identification of ocean-bottom -sedimnents is simiplified by the fact thata limited varlety of %edimentts ('.ariuu, sinimzd, carbonates, etc.) conipriaes a great portion

of he ottm sdimients, of the world'z% oceans (llickmati, 1969). Thus, the nature ofofthe bottontsdm.n -a be rudlit ted in mma-AN intwanec . The %ariouis remnote twnsors,

utsed lit oceantographic resi irch, Int hiding bottu mi in% estigations, are discug.ed byZaitze~ff and Shermant (19%hb. Hicktman (1969)) di,-ct-C.S~e the use )f a pulsed. tiear-blte-

genlaser for ,variou.s hIN drolugmi- and ovenulgra1jhlU applkftiinis including imlenlifica'Fion of buttoni materials ltn iater (if sliallou-to moderate deptR4.

4N

110. STREAM BED GRADIJENT

(a) Definition: A determination of the slope or gradient of tie stream bedusually expressed in terns such as feet per mile.

(b) Interpretation Variables: The gradient of a stream or segment of a streamcan be determined by using the stream bottom or the water surface as the referenceplane or, in instances w here the slope of the land surface approximates the stream grad""ent, the land surface can be used as the reference plane. Gradients can be determinedfor the entire siream on a regional basis or locally for individual ,,.aches.

(e) Remote Sensor Applications: The determination of strt.m bed gradicntsor stream gradients it, general will not be reviewed in detail here. Discussions lartincntI

V to this subject are picsented under other elements in this report, particularly 313 (Landform Elevation), 314 (Landform Slope Angle), 101 (Depth of Water Body), and 109

% (Stream Bed Composition).

itn general, stereo photography would be most useful for determiningstream gradients, tolor photography or panchiomatic with appropriate filters for de-termiining btream-buttum gradients, and panchromatit, for determining the gradient ofthe water surface. Laser profilhrs would also have some application for determininggradients on specific streams. Radar imagery (SLAR in particular) would have sonicapplication for determining reonal gradients of itreams and also regional gradientz ofstream watershcds. In all deterininations, such a, stream gradient,-, both horizontal andvertical references must be maintained.

111. TYPE OF WATER POLLUTANTS

C'Q (a) Definition: A determination of any physical, chemical, or biological com-

ponent of a water mass that alters its natural ecological balance.

c (b) lbtt'rpretation Variables. The evidence of water pollution ranges from theapparent and easily detectabie to that which is mure subtle and difficult to detedt. Thepollution may range from the esthcticall) displeasing but h. rmless, littur to effluents

.-A" %hit-i -contaminate or seveely alte, the ecological balance of a water bod). Floatingforeign material ma) be ,very apparent, abrupt ichangets in turbidity and %atrf colur ma)be noticeable, and even odors may be Atrong. In other c.,e,, pollution charatctristicsmay not be pronounced and only indirectly detectable.

(c) Remote Sensor Applications: Aerial photography has beeni widelq useCdfor pollution studite. The %ariet., of wrntera.-, fim.-S, arui filterts and rxi-ellent rr,•olutionand versatility make photography a very u'sful tool.

"19

9 , , 9 '

UV spectrazonal photography has been used for detecting oil slicks; theoil slick will appear brighter than the surrounding water (Lowc and Hasell, 1966).

Panchromatic and color emulsions wou'd dlso have some value for detect-ing Mi slicks; differences in: spectral responsc as weil ab indirctt indicators of the pres.ence and extent of an oil aL.k such as anomalous wave pattckne, etc., could probablybe recorded.

Sewage pollution has been successfully detected with color and panebro.matic (minus blue) photography (Strandberg, 1964). Color photography is useful fordetecting many types of water pollution. 'Minor tonal diffcrcnvc can be important in.dicators of abnormal conditions in a water body; heated watcr may even show up as

S• distind: tunet, on photography. Color emuhskas are capable of recording a great range

of tones.

Many types of water pollution exhibit distinct colors. Various chemicalsand other wastes discharged into a water body can be detected on the basis of color.The color of the water itself may be altered, or the banks and bottom gravels may bestained. The presence of "ycllow -boy" stains in the streams of the Appalachian Moun.K7rtain mining districts indicates areas %hcre sulfuric acid-resulting from the decompuoi-"tion of iron sulphides-is leaching into the water.

Color and color IR films also allow discrimination of vegetation. Type andvigor of aquatic vegetation can indicate polluted tondition|s and bources of outflow ofeffluents. Increased algae growth is a characteristic of enriched water bodies.

Color photography has provwn valuable for monitoring sediment in waterand for mapping bediment accumulations (Idincidc, 1968, Lohman and IRobilove,1064). Increasing sediment in water shifts uater color toward the greeni (Yost andWenderoth, 1968) and alters tones on IR iensitii e films becausc of increasing reflectivit)of lit. Color IR films are especially useful when [,aze is a problem.

Photography is a useful sensor in itself for pollution studies and is a valuable supplement to other more-exotic sensors.

Multiband sensors have been widely expefimented with for pollution de.tection. Coverage of the expanded, visible spectramn with a va,ivty of film and fiNhercombinations, give-s a good basib for detection uf a %arict. of polhution t pe.s. Such sen-

uor.s .hould be ezqwtialll vyahable for revonnai.stamI 'V work whert a %ariet% of pollutionproblems and :,ources m,,% be encouatcrr d. Multilkand snsors should be useful in a"emg -teral vahtr qAoalit. recunnai',e A stein ,uch a-, outlined bN Strandberg (19154).

20

Mfultiband and thermal scaisor systems are currently being evaluated for pollution studiesby North American Rockwell Corporation.

C Thermal IR s-Insors are widely used for pollution studies. Much of thecfflt.,nts introditced into %. ater bodies are either warmer or colder thani the water bodyitself, and these can be det..cted and point source. can he identified. biodegradeableeffluent also gihes off hea. ýiiich may be detectable in the process of decomposing.Thermal sensors have obvio.~s value for locating discharge paints o; sewage and heatedeffluent from power plants. a~d for studying the dispersion and diffusion of these , ffluento. Thermal 8ensurs also liýc application for studying the natural currents and mixIinlgconditions in e-a~uasiis and lit woral cn-ironments (Stingeliri and Fisher, 1967).

Thermal IR imag..:ry has been used successfully to rnonitor oil pollution([ owe and liasell, 1969; Ester and Golomb, 1970). An oil slick may appear warmeror colder thana mirrountsmng %vatbr depending onl thickness of oil, mixing conditions, suiface roughness, amount of suanshine, time of day, etc. Under ideal conditions, the -.ary -ing thermal response of the oil s'ick may be used to indicate aiffecricncs in its relative,

Thermal JII radiometers are useful for obtaining qwintitative data for Pol,lution sttidiCs dand for establishing the natural diurnal and bcabonat ttemperature regimeof water bodies (Van Lopik, 1968).

Passive mnicrow ave radiometers and imagers serve a fanction similar tothermal HI. imagers and radiomecters. Pollutantb are detected &s a fun.Aion of emissihityteraperature anomalies. Nlifro%%a,.c radiomecterb arc used for nionitoring water-surfacetemsperaturets. Oil slickbshavc beets detected based onl thermal differences and change inwatcr-surfacc roughness associated with an oil-spill area (Aukland, et a!., 1969b).

Rtadar imagery has proven successfu~l for monitoring the extenit of oil slicks(Guinard and Purrvtz, 19710). Other sunsu, s) stews have also proveke useful for detectingand .napping oil slicks. A technique is avcded for remnotel) Jetermnuaing tile ex.act thick-

ness of oil on tile water surface.

UV lasers could be used to stinuidate ltuminescence iii oil-covered water,and flie affected areas could thus be recorded.

"A/

Ganima-ra) and other radiation detector.s would have use for moniuutringradioactne contaminatio.n of %ater bodies, u. for keeping traok of introducwed radio.active sub-statiuct, for dertermining, flovw and di. 1,prrio, t hara~ttcriz.titz. Thlt tuchniqueLs similar to thle use of rhemnicar dyes, as tracer~s.

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112. FRESHWATER/SALTWATER INTERFACE

(a) Definition: A determination of the general boundary between freshwaterand saltwater.

4,• Other elements in this section on Hydrologic Elements have application tothe subject of location of freshwater/saltwatcr interfaces and should also be read (111,116,117).

"(b) Interpretation Variables: Determinations of freshwater/saltwater bound-aries must generally be approximate determinations, because there is probably a transi-tion zone between water which can be definitely considered saline (or brackish) andthat whiuh is fresh (definitions of freshwater and saltwater can also vary). Water bodiesare also dynamic, and boundaries can fluctuate greatly in time.

Such freshwater/saltwater boundaries exist in areas where rivers and surface0 and subsurface springs flow into saline water bodies. Detection of theae freshwater flows

and surface boundaries is made on the basis of a variety of associated surface phenomenasuch as tonal differences caused by quality and quantity of dissolved and suspended sed-iment and differences in temperature and emissivity between the saltwater and the inflowing freshwater.

Frcsh~water/saltwater boundaries or intermediate brackish conditions existalso in many coastal estuaries, marshes, and swamps. Tides, storms, seasonal changes inrainfall, surface runoff, and groundwater levels caute fluctuatons in the location of gen-eral freshwater, brackish, and saltwater zones. The vegetation in the coastal marshesand swamps typicall) reflects the local '.ariatonb in water qualit) and topography andcan be used as a general indicator of distinct zones and interfaces.

/Also, in coastal areas an interface typically exis, s between fresh ground-water and saltw.ater in subsurface aquifers. The position of .his interface can also fluetuate widely depending on a variet) of factors. Various geophysical techniques can beused to detect the level of occurrence of subsurface iater, but it is uncertain whether

- interfaces can be defined accurately by rumote sensing techniques.

(c) Remote Sensor Applications: Tonal differences indicative of freshwater,Naltwatcr, and brackish water areas and interface znCs can be ditscriminated on panchromatic and ultraviolet photography. Multiband photograph) should also be useful fordefining water differences and interface zones.

Color and color IR photography have been widely used for differentiatingfreshwater, ,altwater, and intermediate brat ki~h %ater are.a and interface zones. Subtle

20

,-o

differences in water tones can bt, generail) detected more easily, and the discriminationof vegetation indicators is Also made easier with these films. Color photography ihasbeen used by Paulson (1968) and Duxbury (1967) to determine freshwatcrb!atwaterinterfaces marked by turbulence and discoloration.

In a study of the Everglades of Florida, Schneider (1966) reported on thec-eka delineation between freshvater Mid brackish water marshes that could be made oncolor photographs. Inland tidal estuarinc channels were also easily identified by theirthick assemblages of mangrove trees.

- ~Pestrong (1969) points out the particular value of color IR transparenciesfor studying the distribution of vegetation in a saltwater marsh.

Areas of freshwater flow into saltwater and the location of interface zones

can be ,Ietcrmincd on the basis of temperature and emissivity differences. Thermal infrared a.id passive microwave sensors have obvious application here, and their usc hasbeen discu,,sed by numerous authors among whom arc Snavely and MacfLod (I,.)Taylor and Stingelin (1969), and Wiesnet and Cotton (1967).

Radar imagery pirovides a small-scele format for studying the fluvial/marinehydrologic environment of coastal areas. Shorelines, tidal flats, and mangrove swampsalong the shureline and estuarine ,;hannels show tip well on quality, high-resolutionSLAR imagery (Macdonald, et aL, 1971). These features can be used to separate thefreshwater, brackish, and saltwater areas but only in a very general way.

113. ICE THICKN ESS

(a) Definition: A determination or measure of the vertical d&tance from theair-ice or ice-snow interface to the underlying water ice interface.

(b) Interpretation Variables: To treat this broad subject logically, a distinctionmust be made immediatelv between floating ice (sea ice, lake ice, etc.) and land ice"(freshwater ice in t! v form of glaciers, ice caps, ctc.). Each category could be the sub.ject of a length) anal..si•, in addition, floatiag ice should be dlivided inio freshvwater iceand iew ke bectati of differences in occurrece and physical and chemical properties(and, hence, different effects on clect•omagnetic radiant energy). The dLtinction.s be-tween variui, it c ty pet, are more fully developed under the MGI element 115 (Ice T) pe)

____ and should be read in conjunction with this presentation.

tecentl%, there has been much interest in floating ice especially sea ice inthe Arctic. A nietiing was held in Ottawa, Canada, October, 19 70, entitlee "wSininar

23

K -•on Thickness Measurement of Floating Ice by Remote Sensors." This seminar can beconsidered a slrmmary of the state-of-the-art on the subject.

As with other MGI elements, a distinction can be mad_ between sensorswhich yield direct quantitative data of reasonable accuracy (in this ct5e on ice thickness)and those sensors which provide data by which subjective determinations can be made.

"T hickness determination of sea ice is a special problem, and such dettrniina-tions rely heavily on subjective inferences based on ice type. Such kVdiiiques haveproven satisfactory since mostly class type information on ice thickness (,!.g., 4-8 feet)has been necessary for mobility purposes. Thus, any sensor yielding data wih:ch hrlpsdifferentiate sea-ice types is useful for determining ice thickness; these sensors are dis-cussed at length under 115 (Ice Type).

0 An interpreter knowledgeable of sea ice and its seasonal dcarges, especiallyin a specific area, can make good judgments of ice thickness. Of course, .he adequacyof these judgments would depend on their reliability and on the purpose for whichi theinformation is needed.

There arc also many studies on sea-ice growth and thickness based on air.temperature history, statistical treatments of long-term ie observations, and complex

-• theoretical analyses; thtse are generally limited to specific areas. A listing of some ofthese studies is given by AIaykut and Untcrsteiner (1971). Such studies can aid in thick-ness determinations although the) arc limited in usefulns•t because ice is not a flat, utan-form. static material but it dynamic in all aspects and large %ariation cana be expected.Sea ice in the Arctic can range in thickness from a fraction of an inch for surface glazeto tens of feet for pressure-ridged ice. The biggest problem in this regard is winter ice

L' Io in the open ocean. It is the t) pe of i,:c mn• frcquently encountered and most variablein its characteristiub including thickness and roughness. Snou cover is an additional % ar-iable which .man hinder ice-thickness determination.

(c) Remote Sensor ApplIcations; Photography of all kinds hats been commonlyused for sea-ice type identification. Non-stereo imagery can be used, but sterco coverageis desirable for any detailcd analysib. Panchromatic and panchromatic IR are the mostfrequently used films, but color and color IR films also ha'se %alue especially for sittha-tions such as ice in a melting environment. The age of sea ice can sometimes be relative-

Sly determined on color film, the older ice charattcri-ticall. exhibit- a di.stinct blue color.=Multiband imagery may also have similar usefulnees.

gThickness estimates and, also, direct neasurrments art- possible from photo-

graphic imag-ry of appropriate scale, rcsolution, and metric qualitý. Amiderson (1970)di- ut-,d prot cdurt., for mtasuring upturned llh, k., of it c (.'tanding ftlo'.). lit- ton.idered

24

- . /the imagery scale (panchromatic) of 1.4,364 adequale for the simple measuring tech-/ nique used (calibrated hand magnifier), but he would have preferred a scale on theor ler of 1:2,000 (personal communication). Such measurement, of course, can bemaie more accurately with more sophisticated equipment. The height of pressureribges can also be used as a general indicator of ice thickness.

For lake and river ice, it may be possible for an interpreter knowledgeableabou' these forms of ice to make good c.timates of ice thicknesb. Measurements canprobably also be made of rafted and upturned ice following the procedures t'atlined byAnderson (1970) for sea ice. Color and color IR films may be especially useful in river.ine environments.

For extensive freshwater ice masses such as glaciers, i•e'( ilds, and ice caps,photographl can be used to estimate and measure their overall dimcnS'ons. Thicknessdeterminations, however, will be largely limited to approximations based on the nature"and extent of surface features and the inferred bottom level of the ice mass.

Photography can also be used to ascertain the thielkness of bergs and iceislands-at least that portion above the waterline. Overall dimensions, however, can

* •only be determined b) assuming a given shape for the underwater portion and appl) mngflotation valhes based on the average density of freshwater ice (also allowing for the seaice which commonly occurs on the bottom of these bergs and islands). The accuracy ofsuch a technique remains to be determined.

- •As has been demonstrated, thickness determinations of ice from photogra-ph) depend a great deal on the skill and knowledge of the interpreter. The photograph)is largely a convenient format for diewing the ice couiditi,,ns. Skill is an even nior ;Im-portant factor when imagery from more exotic sensors is used.

S'IThernmal IR and microwave imagery can be used for determinations of sea-Y• ice thickness in rmuch the same manner a. outlined for photograph. - identification of

ice types. In addition, the %ariations in ,ignal intcn.sity can be uwsd as a direct indicator"of ice thickness, although such variablos as snoi oer can tomplicate the procedure.The resolution of these sensors is not as good a. photographN (microwave i6 especihly

~ •poor) and the image geometr, is more complex. Tlwhne-.nsr, however, permit !light.time acquisition of data, and, in addition, tie microwa% c, N'cm is nut significantly af-fected by haze, fog, or clouds. As with photograph), the uisefulness of It and micro.wave imagery depends on, among other things,, the iniage qualuit .,scale, t. pe of ice be.ing monitored, acctracy desired, and the extent of the area of intere-st.

Iiigh-frequenc radar (Si.All) inagerý has bee,; commonl, u..ed for .- a-ic("rz,',mnai.azce. The ,stentiallv all-ueather and da) -night t apabilitic.- (if the SIA Iti make

*1

I'-I

F it a valuable tool especially in the Arctic. Radar permits a rapid reconnaissance of largeareas, and the resolution is sufficient for mapping general ice distribution, types, and

4 large leads, it should be equally as effective for freshwater lake ice. This type of radaris aLho useful for mapping glaciers and ice caps and for locating bergs (some limitations,however, for berg detection-see discussion under 115 (Ice Types)). High-frequencyradar has a limitd penetrating capability (especially on sea ice), and ice-thickness determinations can be made only by the inference procedures outlined under photography.

"U[HF, high-resolution, monocycle-pulse radar has been successfully used tomonitor the thickness of freshwater lake ice (Meyer, 1966; Rinker, 1966). The effec-tive depth of penetration for these systems was about 450 to 700 cm, and ice as thin as11 cm could be resolved for measurement. Test results were good under ideal lake-iceconditions. Problems arise with uneven, inhomogeneous surfaces and interfaces, andthe sy•aem is probably not effective on hummocked lake and river ice. The moroc) cleradar technique does not work on sea ice because of the strong attenuation of radarfrcquency energy by the liquid brine cell- ;ummon in sea ice and the gradual change inbulk-cc density ,ith depth which virtually eliminates a distinct signal return from theice/water interface.

Low-frequency (long wave) radar has been uwed successfully for airbornesounding of freshwater glaciers and thc thick ice caps of Grecnland and the Antarctic(Rinker, et aL, 1966). These measurements show good agreement with data gatheredby ground sismic surveys. There is a decreasing resolition with incicasihg -,avclcngth(antcnna size and other problems), but errors are minimal in relation to t-L. exhfzncthicknesses monitored.

The air.droppable penetrometer has proven to be an accurate sensor of sea-ice thickness (McIntosh, 1970) and, no doubt, can be used for fredhwater ice as well."The penetromctet provides only point data, has a limited depth of penetration in ice,but has good accuracy (within a few centimeters) and may be valuable for specificstudies and prubl.aws especially if low-cost, dibplsable models can be developed.

The laser profilometer can provide valuable data on surface roughness of

sea, ice (ridges, etc.) and extent of open water. Statistical treatments of this data canyield information on ice t) pes from whiuh thicknesse-S can be inferred. This data is%'did, however, unlv for the linear area traversed by the laber, and tupplemental imagery

Iu ouuld have to be used to extend ice t)p,- and thicknes determinations over wider aream.-Th. iLc r profilomcter iDs a comunersiadl) availablc ,cnsor %hidh can operate in daylight,and its data can te stored and treated automatically.

o2

0 2

Other specialized techniques for remotely determining the thickness ofsea ice and floating ice in general are currcntly being experimented with. Some ofthese techniques are discussed by Adey (1970).

Environmental factors affecting the acquisition and interpretation of re-"mote sensing imagery for ice thickness determinations are essentially the same as thosediscussed under 115 (Ice Types).

114. LOCATION AND ALIGN5.ENT OF ICE LEADS, FRACTURES, AND RIDGES

(a) Definition: A determination of the location, alignment, and general dimcn.sions of the major openirgs and lincar zones of weaknews and obstruction occurring onand within floating ice masses.

(b) Interpretation Variables: Recognition and location of the above featuresare important for ship travel through extensive sea-icc cover, for surface travel acrossthe ice, and for aircraft landings on the ice. These mobility problems affect freshwater

0floating ice as well. Ice on small streams does not present the same problems as ice on- - rivers and lakes, however, it is still desirable to know the distribution of ice, open w, ter

areas, and zones of weaknew, and roughness even on small streams.

Sea ice can serve as an approximate model for the above features. It is themost extensive floating ice t) pe, reacbes the tgreatest thicknuss, and contains the moststriking examples of ltads, fratture:,, and ridges. The conclusions reached as to effective"sCnsoys for reconnaissan,.e of these features on sea ice, hupiefully, can be applied tofreshwater floating ice with appropriate modifications in scale, etc.

Ridges are a type of pressure ice and are formeJ when, because of compres.sive forces acting within the floating ice mass, floes are pressud togethei and forced up-ward along fracture zones. The) may reach several tens of feet in thickness. The ridgescan be identified by their irregular linear patterns, sertical relief and roughness (whichmay be highlighted b) shadows), and associated snow bank6 which tend to form againstthem.

Other types of pressure ice can also occur: Ice floes may override oneanother (rafted ice), noes may be upturned and wedged between adjacent floes in avertical or near vertical position (standing floe), or ice ma) pile up in a jumbled mass.,"(h'anmmocked ice). Itecognition arid location of all types of pres.ure ke are importantfor mw*bility purposes.

V ariable forcev, acting within the shifting ice mass also give rise to numner..ouis fractures. These car be rrack.s of little displacement or large niavigable openings, or

; oI

- - - -- - - -

leads. The leads may subsequently freeze over but the ice cover will •e generally thinnerthan the surrounding floes. Leads can be detected and recognized by their characteristicelongated pattern and contrast between open water and adjacent ice. Differences in re-flective and thermal properties of the ite/water interfaces provide the bsais for detectingleads with a variety af active and passive remote sensors.

imaging sensors are the most useful for detecting leads, fractures, and ridgeson floating ice. V ith imagery (stereo especially), the linear patterns of thesw features canbe readily recogrized and their distribution mapped.

(c) Rf.,mote Sensor Application: Photography of all types can provide informa-tion on location, alignment, and overall dimensions of leads, fractures, and ridges. Pan-chromatic anJ panchromatic III are most commonly used. Anderson (1971) gives anexample of the use of large scale (approximately 1.4,400) panchromatic photography

" "-(stereo) for a detailed analysis of leads, ridges, and general ice conditions in a local areaof the Arctic Ocean. Measurements of ridge heights, especially, require large-scale stereoimagery. Generally, leads are more readily identifiable on small-scale imagery than arepressure ridges. Panoramic photography has proven to be especially useful for sea-icereconnaissance (Biache, et al., 1971).

Color and color IR can provide additional information and contrast (espe-cially on leads) where maximum definition is needed between snow, ice, and open water.For similar reasons, mull-;band ph-'. ,graphy would also be useful. Use of these moreexotic films and tecimaques, however, would have to take into consideration cost andother factors which may limit their use to local areas and special ice studies.

Low-sun-angle photographic techniques may help to outline ridges l*ndother relief features on the ice but would be less desirable fo, detecting leads. Special,low-light-letel photographic systems fnuy have usefulness for acquiring imagery undertwilight conditions and even at night under optimum atmospheric conditions.

lR scanner imagery can also be used to detect ice leads, fractures, andridges. Open leads especially provide excellent thermal contrasts. Areas of thin ice

i 0 should also be generally distinguishable from areas of thick ice -the thinner ice areas"exhibiting generally warmer tones on the imagery. Variable snow couer and meltwaterpools on the ice, however. -.an minimit. thermal contrasts or cause anomalous signals.Such environmental fact,)rs ast these, ats well as diurnal and scasona! hlanges in the general ice environment, must be kept in mind when anal) zing ice conditions on IlI imagery.Pre&surte ridges, for instam -, nurmall. appear ",old" oin nighttime alw. diffused daylightimagery, but under strong sunlight the sun-oriented faces of the ridges ( an give verywarm returns.

24

-'- 'I-

- -- :

Microwvave scanners also permib. imaging of ice conditions at nighi anwI"tinder atmospheric moisture conditions that would inhibit use of n--.rmal IR. Spatialresolution is poor; but large features, especiaily leads, should be readily detectable.

- ,iicrc,, ave energy is not totally unaffected b, atmupyheric moistre; however, lowcd ),u cover, for inptance, caii raise t'he microwave brightneis temperature of water(hits low emissivity and normally appeans cold) thus less.ning thet contrast betwe'n iceand snow.(Strong and Fleming, 1970).

Televison-type sysTems have good resolution and are useful for monitoring

ir ice conditions in real tirlie, permanent images can also,'bc obtained. Such sensors canbe a valuable part of an overall ice reconnaisbance s)stem as outlined by Harwood (1968)

-and Biache, el al. (1971).

Radar, especially SLAR, peimits the rapid imaging of sea-fce conditionsover wide areas. Despite generall) small scales and limited cntrast, ice ty pes can beidentified, land margins outlined, large bergs-, floes, and ice island, idcntifd, and inter-vening leads detected. On qualit) imager% of larger scale (depending on ty pe of radar,scanning ninde, altitude, etc.), large pressure ridges can be identified and trac -d.Anderson (1966) shows examples of cunventional, high-altitude radar imagery of seaice and discusses arious fe. tres which can be identified. Use of stereo radar imagerywould greatly enhanv. the analysis of ice features-especially pressure ridges.

Leads, fractures, and ridges ma) be identified, and their distributions maybe mapped from qualit) photographic, imagery b) a less-eperienced interpreter. This

is generally true, als), for scanner and radar imager), however, there will be instan•t.swhen, because of anomalous returnts, etc., an interprctet i ill be needed whu is familiarvwith the basics of these senoors and the effects of environmental variables.

Airborne laser systems can provide valuable ,tatistical data on frequency.of occurrence and• vertical diniens.ioun (le, teliable for hotiiontal diinmn.sions) of iceleads, ridgea, etc., over a given Wlght path. The difficulty of maintaining azimuth andLnowv ing trut ground speedl howner, giie.- ri.se to lucation problem., and lcessns theutility of the laser system for detailed studies.

Some diseuti.,sion has alread% becn made of the environmental variablesSaffecting th.- mu quiiition and interpretation of rn-mot srensor imagery for the purpose

of dt tectIng and recognizing ice lead.s, fratuturev', and ridges. Other environmental"X, factor., (onminon to ire reconnaissance are discu.-,ed un(d'r 115 (ree Type).

/

115. ICE TYTPE

(a) Definition: A determination of the type of ice mass based on origin.che•nical and physical properties, morphology, and stage of development.

(b) Interpretation Variables: This is a broad categcky and for any detailed

discussion should be subdivided into several subcategories. Sea ice alone would meri.individual attention. An attempt, however, w ill be made to cover the major ice typesalthough sea ice will be discussed in more detail than others. Major ice aecumelations

Y/ can be divided into land ice and floating iv". Floating ice can be subdivided into fresh.water and saltwater ice or sea ice. Floatimag ice is the most widespread type in arealextent-sea ice alone making up nearly two-thirds df the earth's ice cover (Maykut andUntersteiner, 1971). The freshwater floating ice cover fluctuatee greatly with seasonalwarming and cooling an. generally disappears in !akes and rivers even in 1111 hf-l alti-tudes. The sea.ice cover, confined largely to the polar latitudes, altA fluctuates season-ally but not as greatly, and a vertain portion-the polar ice packs-remains from sesonto season.

Bergs and ice islands are special forms of floating ice. These are masses offreshwater ice derived from glaciers and ice shelves of land areas. The bergs and iccislands can be of great dimensions (some ice islands in the Arctic Ocean arc used asfloating scientific observatories) and commonly have saltwater ice attached to theirbottoms.

Land ice .s freshwater ice occurring as small seasonal accumulations and aslarger more permanent masses on thl land surface. Considerable ice also occurs %%idLinfrozen grouad, but this mode of occurrence will ntt be discd% here. Land ice canrange from small ground-water-fed icings a few feet thick, to vcr, thick ice in the form

9 of glaciers and icefields, to extremely th:,k and c.x.asive ice caps. The Greenland icecap, for example, covers an area of about 666,000 square miles, averages about 5,000feet in thickness, and reaches a maximum th:ckness of about 10,000 feet (Bader, 1961).

The identification of general ice types is rlatively straightforward sincethe location and mode of occurrence indi., ate its origin and composition. Such general(1, terminations will be treated onl) briefly. General treatments of the g.-ographical andgeomorphological aspects of major ic, forms arc given b) Thorubur (1954) and Flint(1957). Glaciers are considered in more detail under 310 (Locat;,on of (laciel's).

A brief classification of major sea-ice types, presented below, is extractedfrom the compre'hensive manval "NIANICE" (Amendenct #5) pubhh-hed b) the Canad-ian l)epartment of Transport, 1965:

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A'O

New Ice: A general term for recently formed ice which inclu4esSfrazil ice, greas'ý ice, slusl, and shugga. These types of ice are com-

posed of ice crystals which are orny weakly frozen together (if atall) and have a definite form only whil'- 'hey are afleat.

Nilas: A thin elastic crust of ice .eading on waves and swell andunder press..ae, thrusting in a pattm-n of interlocking "fingers"1

""finger rafting). Has a matte surface and is up to 4 inches in4 - thickness.

Young Ice: Ice in the transition stage between nifus and first-year ice; 4-12 inches in thickness. fFirst-year Ice: Sea ice (f not more than one winter's growti,

0 > developing from young see; thickness from 12 inches to 6 feetor more.

Second-year Ice: Old ice which has survived only one summer'smelt. Because it is thicker and less dense than first-year ice, itstands higher out of the water. In contrast to multi-year ice,"summer melting produces a regular pattern of numerous smallpuddles. Bare pa,ches and puddles are usually greenish-blue.

NMulti-year Ice: Old ice up to 9 feet or morc thick which hassur•4ved at least two summers. Hummocks are smoother thanin second-year ice, and the ice is almost salt-free. Color, where

-~ •.bare, is usuwlly blue. Melt pattern consists of large interconnect-ing irregular puddles and a well-developed drainage system.

The first-year, second-year, and niulki-year ice are of special interest sincethese t)' pes are the thickest. Thcsc ice ty pet have characteristic patterne which serve toidentify each. The mulli-year ice, for instance, is characteristicall) extremely jumbled,broken, and pressure-ridged; it makes up the bulk of the "pack ice."

Freshlvatcr floating ice. can also have similar classifications (the terms multi-ye, ice, osecond-yea. ice, etc., however, do not, gencrall), apply to fredhwater floatingice). In fact, nitch of the ternimolog3 used tu describe freshwater ice is similar to thatused for -- a ice (Michel, 1971). Man. teatures buch as hummocked ice and panc-ake ictare comu:l;n to both ice regime.,. Suc-h conmnon ice term., a. e dc.crihed n numerousglossaries simie of which are listed by Mlichel (1971)

(91

The identification of the various types of sea ice is an important problem.Much of the information that is derived on eea ice through remote sewsing techniques isdone by the identification of major ice types. Many attributes, such as thickness androughness, are associated with specific sea-icc types. Generally, only broad class4ypedata is required (for example, thickness class 4-8 feet), and much of this type of infor-"marion can be obtained from remote sensor imagery on wh:cd sea-ice types can beidentified and distributions mapped.

0 •'(c) Remote Sensor Applications: Photographic systems hitc commostly beenused for general investigations of various ice types and forms in Al en ironments. Thestinvestigations range from general reconnaissance mapping to specific dIctailed anal) "ib.

0, " Measurements can also be made on stereo photography. Uscfui scales depend on thetype of ice being imaged and the information requirements, but, gtnerally, use ' sakscan be quite small.

Panvhromatic and panchromatic iI arc the most commonly used films forice studies, but color and color IR films can provide much additionad information especially in tituations such as ice in a inciting environment (goud definition of pondedwater or- :ce), local icings, and iev on rivers where good boundary definition, are re-

Squirtad. The relative age of sea ice can sometimes be ascertained on color fi!,.i-theolder ice exia,•iting a distinct blue color. Limited exposure latitudc, however, tend torestrict the use of color films in polar regions.

/ Acquisition of photographic imnagtry is usually lrgely confined to day.light and io rclatieiy clear atmospheric condi1ion.,. Special low-lighlit, camera-filh ,.stemi may permit imaging of ice at night under special conditions, e.g., full moan ahdclear atmosphere. Visibilit, over ice at night under suih ideal uonditions (.an be %cr)

N' good.

An example of the type of detailed analysis thaO can be carried out on seaice using large.-cale panchromatic photograph. is provid(-d b) Anderonu (1970). hct

- ty pes arc identified and dibcused and thicknK% mncasurermcntts itade on upturned ..e)s.

•Thermal 1R aminner imagery has been used for investigation of a variety ofbroad ice t pez. Spatial and thermanl rt-,olutionms are good. "l'he o.patiai retsolution ofconventional unclassified ,, stems cau be on the order of 1 fokot in -i 1i,000 feet andthermal resolution, on the order of .5" C. Neivri systems probablN ha," egreatcr sensi-tivitiens. The 1R scanner ,an be useId as a prime senior or a.s a .nuppkl, m ,ar-nyeor topho!ograph,. IR radivneters can also add ialuablt qtwAntitatikv tlhermal dat,.

"UIse of lR iniagery ra•tge- from detectingg ev.r:%ea.vs on glacier, and l-t, flp,"ito -tudt ing the thetrmal regime' of icr-ovcred ri%-'r.-. \a\inuin cffc• t4,% .. ,., gainted

32

" '

by acquiring imager y at times wh,;zi signa! contrasts will be greatest which may be atvarious timeduring the day or night.

The thermal IR -canner has proven to be a useful reconnahisance sensorfor sea ice. Ice types cart be readily identified, and, under good meteorological condi-tions, high altitude flights can be made ?nld wide coverage obtained. Use of AR imagery;;',-o allo-s- tile detection of frozen, snow -covered shorelines of low relief which are not

)>read&~ observablc or arec ompletely undetectable on conventional imagery (Pouliam andHarwocd, M966; Poutiin, in preparation). The tcc~anique should also work in similar

* freshivater situations.

oVSea-ice types are identified from IR imagery by tonal contrasts indicating

differences in thermal respons~e and by surfac ruhesadtlricc pattrns. Whlile,in general, thermal signals will be a function of ice thickness (thick ice appearing colder

qýthan thin ice), variable snow cwvcr and variable scasonal and meteorological m'nditioiiscan affect the thermal signal. Reliance on tonal contrast alone canl yield mw~eadingdata onl sea-k- types. Such fa-tors limit the tisefuln ms for sea-icc type identificationof dita obtained .automatically from dens',ty traces of JR imagety or from direct proc.essing, of thermal tignals.

The most -,ommonly used thermal JR band is thle 8 to 14 rnicromn*tcr handwhich in its tipper limits;,; a "window" band to CO2 in addifion to Hl 0 and 02. JRradlialt energy is not totaliy unaffected by atmospheric moisture, however; and it issometimes desirable to fly a., IR spectrometer in conjunction wi#"z a seanlner to deter-mine thle degree of attcnuatioiv of the thermal Irt signal, especcially at niight when it isdifficult to judge atiaospheric cotditions. Thei use of JR speckrometer bands of otherthan "window" wavelengths will give indications of atmaospharic moisture conditionswhich canl be allowed for in thle erawiter imllgery.

Passive microwave scarnra-is hraw~ also beeni used for sea-ice reconnaisAiancees4pecially by the U. S. Coast Guard for detection of icebt Wýgs inl heavil) used shippinglanes (Hlarwood 1969). Despite poor spatial re.:olution, micruwavewsanners are usefulfor berg detcecion because radiant zmergy at mnicrowave frequencies is ezicentially unaf-fected by thick haze or fog -a condition which exists over areas such as thle GranldBlanks for much (if the iceberg season. Inl addition, microwave imagery call be obtainedat night. However, microwave has sonic limitat ions for berg detection inl that the~ titer-mil "brightnt-ss" of anl iceberg canl have a -ai&d range and the berg call be confu~sed withit ship having a low thermial output (Hat wood, 1969).

Mlirrowame si-afners should be uteful als o fr delineating frozen, SHOW-covered shorcline~s in a ir miter simsilar to thermnal Ml. Currentl1 . there is mxuch inl resit

33 ;

in ar~d experimenting with micrcwavc stasing techniques (Porter. 1970; Porter andFlorence, 1969).

Radar is also used for bcrg detection but is limited in usefulness in shippingareas in that it sometimes gcnerates similar returns for ships and bergs (Harwood, 1969).Despite some shortcomings, ilvighfrequency radar, in particular SLAR, is a widely usedsensor for bca-ice reconnaissance because of its all-weathet day ,'night Capability and itsability to image large areas on small antounts of film. Despite limitations in resulutionlavid tonal contrasts, gross surface patterns canl he detected, ice types identified, and dis.tfibutions mipped rap~ily on radar imagery. Many different radat systems havwe beentused for sea-;ce reconnaissance using various bands (X, Ka), and IMUlIfrequetmy bandshave alsu bccn experimented with (Guinard, 1969). Radar can also providie good cover.age on the distribution and major features of freshwater lake ice and cain be used formapping various large-surface features and boundaries on glaciers, ice sheets, and icecaps (see element 310 (Glaciers)).

TMe radar scatterolueter has also beeni used to identify sea-ice types basedon differences in scattering coefficients in the 2.25 cm wavelength band (Rouse, 1968)'.

The laser pro filomieter canl be used for dif ferentiating sea-ice types basedonl surface roughness. The system yields only line trace data, but these data can bestored and processedl automatically -a valuable feature for rapid mapping of sca-icc

types. The possibility of developing 4 laser scanner has been mentioned by liarwood

%antagcb %thich would have to be reconciled. The latser profiloineter canl adbo yield valu-able data on surface characteristics of ice othcr than cica ice, but it wvould not be used asa primary' sensor for identification of the~se other broad ice types.

The environmental factors affecting thle remtote sensing of various types ofice have been &iscut";ed briefly in relation to ,omne of the indiiidualwrsensr sseThese environmental fact,-rs are mos-tly nietcorolugice11. lhize, fog, and clouds affect thea~quisition and interpretability of ph..tographit iniagcry, latser traces, tuid thermal IIIimtager . Nighttime operatiows are largely lintiterl to radar, microwavc., and thermal IR

sesrappreciable atmuo.pheric tvater iapur, lhowe~er, restrictts the !fighttime use ofhermnal filt ,en~sors. AcIU6iousin of r, mote qenwor iniager8 in thle polar regions is eumpl.

(ated bN flung periodi. of tiarknv.ess during thle %%inter and a1ppreciable clo-jd co~er duringthle s'ummter.

1% itubs are atnother eiivironnwnvttal factor lbecatJp thie% canl eraset surfacethirnil sgitlsand cduse drifting of ,mts%. Vai itbiv thivknvmess of snou co~er on land

:int itt c-an na~k minor mirfavc features and tint cal fradures,. smih %ariatiuns oftsnou-thirk'knes and tnit all also tý%v rise to anomalou.s thermal and rad~ir signals.

.5M

Temperature inversiorns. especially at night, can also give rise to anomalous thermal sig-nala. Sudc environmental fac'or- must be kept in mind when a remote sensing missionis plan-cd or when imagery is analyzed.

116. LOCATION OF SPRINGS

(a) Definition: A determination of the location of groundwater issuing from"a natural opening in suck quantity as to make a distinct flow. I.

coo There are other elements in this report that contain information pertinent'A to tke detection of springs, these should be read in conjunction with this presentation-•.particularly 307 (Soil Moisture Content), I111 (Type of Water Pollutants), arid 120 (Lo-

"cation of Groundwater).

(b) Interpretation Variables: Water from springs may issue on the land surfaceor flow directly into a watcr body such as a stream ur lake. Various vegetation assem-

,___, blages may iniicate the presence of springs, especially ii, arid regions. Springs issuinginto water bodies may give rise to distinct tones because of diffcrences in water quality,etc., which maiy 4- detectable on remote sensor imagery-particularly photography.The springwater frequently is at a different temperature than the water bud) and is als-detectable on this basis. Differences in enuissivit) also make detection possible particu.

.o � larly where freshwatcr springs issue into saltwater bodies. The 6enterall) limited volumeof flow from springs can make thoir detection difficult; large-scale imagcr is generallydesirable. It way be ad%antageous to acquire imagery during dry period, when springsshould theoretieallh be more easily Jetected and (thcr types of water flow reduced.

(c) Remote Sensor Applications: PIhotograph) of %arious types can be used torecord and identify the indicators of springs. Color and cIodr IR tilms have special usefor locating springs having assotiated azseniblago, of lush ,vgeatioia. Color and color IR

o films are alko especially uw'ftil for detccting the stubtle tonal differenc,- in watc" bodiesthat may indicate the presence of spring-,.

K. l.iltiband photograph, can provide a broad ba,,is fon rcconnai,,sance detce-tion of springs occurring on the land zurface and in water bodies.

Thlermal Ilt imagen ha. s been widely ue.,d to detect springs. Both the 3- to5.5- and 8 to 1T-micronwter bands havime lcn vmploy ed. Lee (1969) lhas bee•n able toSdetect springi di.,charging into Mono Lake, California (a slint lake). The flow of ,ome

S-springt, wavs as Iou av- a fcv% liters per second. In main occanic coa.tal areas. ,uch as ittliavsaii, Iresh groundvater flonsing into tit, ot ran ha- beun do',t ted bh thrrmal uinagcr.G(;e-othcrmal springs it, the Yellostonc Park area hawtc a!-o breen detected on thcrai.J

35

imager). Stingelin (1969) notcs that springs are especially detectable on nighttime,winter thermal imagery when air temperatures are well below freezing.

Satte Passive microwave imagery can be used to detect springs in a manner simi-

far to thermal IR although spatial resolution is not as good.

Radar imagery, particularly SLAR, can be useful for detecting springs andfor vv ater-resource investigations in general. The imagery provides a •mall-bcale layout

4 •,of the major features of the landscape, such as topography and drainage, and can beused to cmaluate the broad conditions of overland and subsurface flow- incduding lilclocations where springs may occur. Only very general determinations cdan be made,however, and other types of imagery or supplemental information must be used.

0

117. LOCATION OF GEOTHERMAL WATERS

(a) Definition: A determination of the location of surface water that hasissued from the subsurface after being heated by geothermal soirces.

(b) Interpretation Variables: Geothermal springs and other hydrothermal fea-turcs such as geysers occur in generally restricted areas on the earth's surface. Theirmost distinguishing characteristio: is •he abnormally high temperature of the wvater.IMany of the methods and techniques used to detect springs, seeps, etc., of normal tem-

0 perature (see 116) can also be used to detect their geothermal .( ,nterparts, however,the most obvious way to detect these featurecs is to employ th rmal sensors.

(c) Remote Sensor Applications: Thermal infrared st a'ner imagery has beenwidely used to detect geothermal wvatcrs. Bloth the 3- to 5- and 8- to 14-micrometerwavelength bands lha,- been employed. L,,rge.,scale imagery is desirable. Imager) can"be obtained at night or early morning %i hen the conthabt bctween| thermal water: andsurroundings, is greatest. MLcrrait (196,7), lbouscir, ha.s .hown that imager) obtainedduring late morning has the best potential fur differentiating betwetn geothermal andnon-geothermal springs.

Geothermal waters characteristically exhibit greater than normal amountsof radioactivity and may aLo be detectable on this basis.

118. AREA OF SWAMP

(a) Definition: Area of water-..turated land dominated 1, trees and .,hrub..2

- - 21fpzl2wi it of dti Arrn•,, 1959. "Yfrrfan hnidllih,.'nc" \ltmil t.i 39.10.

:16

?. t3

(b) Interpretation Variablest. To estim ate or measure the area of a swamp,marsh, or similar wetland feature, the feature must first be recognized, identified, andbounded. Determining ex~act boundaries canl lie difficult; however, therc is generallyenough topigraphic variation associated with a swamp or marsh to allow delineationof major boundaries. The geometry of various ty pes of remote sensor i agcr fora a-curate measurement of area is brir~fly discussed under "Area of Surfl,;ial Deost (303).

Aerial photography has been commonly used in the past to investigateswvamps, marshesb,and wetland arcah in general. Patichromatic photography hab proba-bly- been the most commonly eniploy ed. Ini rucent y ears, color and color IR photogra-phy have been inercasingly utilized,. These film!, have obvious advantages for study ing,the varied elements of wetlanid tcrrain. Recent work ha!, also beeni directed toward theautomatic interpretation of -,wamps and marbshes. Multi:spectral data in 10 bands, bc-tween 0.4 to 1.0 micrometer obtained from a flying hecight of 2,000 feet Las been auto-matically processed to outline owanips (Kolipenski, et aL., 1969). Waveformn analy~soeof grey- tones of infrared imagery and panchromnatic photography have been applied tothe automatic delineation of swamps (Latham and Witnecr, 19679).

()Remote Sensor Applications. Ani evaluation of multiband photography(nine lens camera. bands between .4 anid .9 miurometei) and ,upplentenital phoutograph)(panchronmatic, Ek1tachrome. and Ektachromec IR) was carried out onl a tidal inanih areain San Francisco Bay by Pe~strong (1969). Some of Itills conclusions were:

1.1) Near infrared photography was superior for detection of drainlagechannels and for determining boundaries between land and water.

(2) The Ek1tachrome lit photography was superior for differentiationl ofthe various tN Ile,, of %eggetation in the marsh. There was a close correlation In-tweeiiVegetation types and marsh topography .

(3) For overall interpiretive purposes, Ektachironwe color tran.,parieneleswere most useful.

Smith~ (1963) point.- out the usefulnes-s of color 1lmotograph% for dlrlincLat-Is 1,ing s1wamnl. and marshes and thevir drainage patterns.

The-rmal infrared rcanning devices, employing the 3- to 5.mnicrometer hakilhae ee app~lied to thec ,Iuds ofmswamp% aream (Stingein19).Te inifrared images

clearl% di~ ingpi6li thet areas toi sat uratt dl grounnd. kii infrart-d sumtr%( , hould hprolbalily0 - be artinimpalmied I)% soinvc I% p~c (i jl41otgraldiN to (i arl% dep~i.t Itrees ,andt i'Ilr I% p0-s

of %egetatiomin.

119. AREA OF MARSH

(a) Definition: Area of water-saturated land dominated by Lrass-likc, aquaticvegetation.3

(b) Interpretation Variables: Much the same considerations opply to the de-lineation of marsies as to swvamps. For the remainder of this discussion, refcr to "Arca

'W of Swamp" (118).

(c) Remote Senior Application: Refer to (118).

12.,. LOCATiON OF GROUJN IWATER

(a) Definition: A detcrmination of the presence in subsurface strata of a water-T' saturated zone.

(b) Interpretation Variables: The upper !,mit of the zone of water saturationin rocks and soils is known as the groundwvater table. iHe depth of occurrence and itsfluctuation it, an area depend on many fao-torb soini of which are climate, topography,and structure and type of rocks and soils. A regional groundwater oable may exist inan area along with many local "perchied" zones of saturation at levels abut t; the region.al table.

Determining the presence and depth of groundwater in an area from re-mote sensor imagery is largely an interpretive procedure requiring the skills of an ex-perienced %vorker. Many complex observations arid judgments iuist be made. An areamust be considered in total because of the many factor-., determining the occurrenceK . and depth of groundwvater. The interpreter utiliztc, nunmero•s clue, in determining thepresence of ground%ater ;1nd it, probable depth, these include drainage characteristics,"the t) pe and distribution of vegetation (c.spetiaIi) imporhtd in arid regions), land mue,avd cultural features suvh ab artificial ponds, ditches, and wells. Special attention ispaid to plains and valles and loui area., in general. The surfaec matcrialts are cvaluated,"and areas of exccive soil moisture or s-tanding % ater ar,- noted. l losv (1938) oufliatvsOA comprehensive procedure for evaluating the groundwvater conditions in all area.

"Oi.• i cemnt.s in this report al,,o contain information related to the gen.cral subject of location of grotndvater, vspcciallh 307 (Moisture Content of SurficialSlhposit) and 1 1 (Locatiomn of Sprivg,).

o = 0

I3epaifniLta of tihe. ,Arnn 159A, "1 .,In Inti•ct• ces," w |M .InuI I* •, 30-1).O

3H

(c) Remote Sensor Applications: A variety of remnote bensors can be used toprovide data for interpreting grouindwvater conditions. Probably the most widely usedis photogrnphy. Photography proVides a con-,enient. format for viewving the lanrdscapeas it appears naturally (especially true for color photography). Small-scale photos (ormosair-s) can be used for a regional analysis, arid photos, of larger s-cale can be used forfinvestigating local conditions of groundviater occurrence. Such a regional-to-local ap-proach is advocated by Howe (1958).

Panchromatic atnd panchromnatic IR films can be used ad-Vantagcously forgeneral groundwater evalu.-tions (Hlowe, 1958: Chase 1961). Because the interpreta-fion of groundwater conjxi!ions in an area involves the evaluation of many diversenatural and cultural landscape ft-!ures, it iuould appear that color anid color IR filmswould generally yield the best overall rt-zults. Tht inerits of these films in terms of easeof recognition anid interpretation of soils, sod m~oisture, drainalge, vegetation, anid cultu-ral features have been discussed in many articles.

Sclrreder (0968) mentions that the proper identification of key indicatorsof subsurface water may be enhanced by the uise of color photography.

Mlultiband phrotographay would also be useful for ainalyzing grou.-sdwrterindicators in (bvcrse terrain.

TIhermal IR anid passive microwave imagery can provide useful data forevaluating groundlwater conditions. The imagery is probably best used in] conjunctionwith photography. The imnager) can aid in loeating drainage features suc:h is- smal"wate~r bodies, streanlis, sceivs.and springs and for evaluating relative soil moisture levels.

VL !areas of htigh-.surface soil moisture c-an produce distinct thermal tones in 111 imiag-cry; such areas~ mary have locally-shallow water tables. Subsurface soil moisture canalso influence the surhu e temperature andl tit-. general nature of subsurface materialsindicatted by sin-fact- thermal responses. Coarse. well-drained materials such as sandsanrd gravels rimay have lit tie surface moisture but contain appreciable groundlwater atidepth. Wernitind (1971-) reports good correlation of inicrou ave anid thermal IR radioni-cler ineasurvinrents over known £rrotincllater sits in arid terrain.

Care munst be taken when anralyzing thernial hinrageri- that tone-sare nothastily ittributed to thie effi-ets of soil moisture. :ýtich misleading tonesi can be pro-K.rucedi, fvr in~stance, IN the pooling of cold air in lovs areass as repossted by 11 olfe (19611).Imaging mis~sions Ahould be lplanntrt~d to obtaiun miaxiniumn contrasts, of ground signals.Good etsults have been olbtained with imagerv i-quired a few hours before dawn. Fact-

or.; thaf Itu(!' heonsider.-d when planning it thermal urissiomi iclude the( tN Iv of area,genrera! nature of st.~-favc materials; and wgttin esaand pre-~iou.s mnwi-tori4ogrical

r ~39

/l

-4

Radar imagery, particularly SLAR, has some use for inferring the presenceand probable depth of groundwater in an area. The generally small-scale imagery allowsain appraisal of the major components of the landscape which arc important for evaluat-ing groundwater conditions. These include topography, structure, dzainage,. -ross vege-tation types, and major soil and rock units. The chief value of the radar imagery, thus,is for appraising the overall "setting" of an area. Other types of remote sensor imagery,

-. ' such as photography, will be nteded to make more detailed and ri-ble determinationsof groundwater conditions.

Indications are that surface soil moisture in general affects the strengthand polarization of return radar signals, parficularly at shorter wavelengths. Teats byDavis, et a. (1966), indicate that long-wavelength (P band) radar bignals --anl withinlimits penetrate soils, and the prtsence of groundwater can be detected by dharacteris-tic reflections from the subsurface soiiAatcr interface. Such preliminary results showpromise for radar as a tool for remotely determining by direct means the soil moisture

"K and groundwatcr eonditi6ns of terrain.

Various airborne and surface geophysical techniques have been used forldetermining the presence and depth of groundwater. Among the relatively ntiw air-

borne techniques are the INPUTl system reported by Barringer (1966) and the E-PhaseITM system reported by Barringer and McNeil (1971). Adams and Lepley (1971) reportoon the use of a around based Aidioniagnetotelluric s).tc::. it.:, !tswaii for determiidngthe depth to groundwater and for making -t!hr judgmentbs on stbsurfwce characteristics.

The air-droppable penetrometer ma) also have application for determiningthe depth to groundwater at a given location.

0 • b. References and Bibliography for the 100 Series.

101-1 American Society of Photograminitry, 1966, Manual of Color"Aerial Photography. First E6,.ion, Banta Publishing Co., Mua.ha,\wisconsin, 550 pp.

"101-2 Ctonrad, A., et al.. 1968. "A crid lPhotog-raphy for Shallow \\ aMelStudies on the WVest lElge of the Bahama Banks," Report ,;f Experi-mental A:.ronomy Laboratory, M.I.T., Cambridge, Masail-huwtts.

101.3 (;eary, E. L., 1968, "Coastal llydrograplhy, PhotogrammetricEngineering, \ ol. 34. No. 1, pp. 44-50.

oto<1,li

'I"

ýA'

1014 Joering, E. A.. 1969, "Estimating Streamflow Characteristics UsingAirphotos," Technical Note, U. S. Army Cold Regions Researchand Engineering Laboratory, Hanover, N. H.

101-5 Krudristskii, D. M., Popov, I.V., Romanova, E. A., 1956, "Hydro-

graphic Interpretation to Investigation of Aerial Photograplis,"- : Translation from the Russian by Shmutlcr and Stock, Israel Pro-

gram for Scientific Translations, 1966.

101-6 Lepley, L. K., 1968, "Coastal Water Clarity from Space Photogra-phy," Photogrammetric Engineering, Vol. 34, No. 7, pp. 667-677.

101-7 Lundahl, A. C., 1948, "Underwater Depth Determination by AerialPhotography," Pihotogrammetric Engineering, Vol. 14, No. 4, pp.

'1 454462.

101-8 Meyer, W. 0. J. G., 1964, "Formula for Conversion of Stercoscopi.cally Observed Apparent Depth of Water to True Depth; NuinericalExamples and Discussion," Photogrnnmnefric Engineering, Vol. 30,No. 6, pp. 1037-1045.

101-9 Moesner, K. E., 1963, "Estimating Depth of Small Mountain Lakesby Photo Measurement Techniques," Photogranmnetric Engineering,Vol. 29, No. 4, pp. 580.589.

101-10 Polcyn, F. C., Brown, W. L., and Sattinger, I. J., 1970, "The l.ea-surentent of Water Depth by Remote Sensing Techniques," Report8973-26-F, Infrared and Optics Laboratory, Willow Run Labora.

tories, Institute of Science and T'cchriology, University vt" Michigan,38p. (Prepared for U. S. Naval Oceýawgraphic Office, Washington,1). C., Contract N62306.67-C.0243.)

101-11 Poh'yn, F. C. and Sattinger, I. J., 1969, "Water l)epth Measure.j11. lnls Using Remote Sensing Teccuniques," Proceeding"s Sixth Inter-

.... i...ai Symposium on Remnote Sensing of lwnvironnent, Jlliver•ityof Michigan, pp. 10 17.1028.

101-12 Robinove, C. J., 1968, "The Status of llemnote Sensing in llvirol.og7," l'roeeedings Fifth Simlposillull ol Remote senlliiig of Ellviroln.uiient, Universi,( of Michigan, pl. 1127-831,

-t II

____------- '____

- IA

7K

101-13 Ross, D. S., 1969, "Enhanced Oceanographic Imagery," Proceed-ings Sixth Internationai Symposium on Remote Sensing of Environ.ment, University of Michigan, pp. 1029-1044.

101-14 Schneider, W. J., 1968, "Color Photographs for Water Resource• .- ) Studies," Photogrammetric Engineering, Vol. 34, No. 3. pp. 257T262.

101-15 Sonu, C. J., 1964, "Study of Shore Processes with Aid of AerialPhotogrammetry," Phlotogrammetrfc Engineering, Vol. 30, No. 6,pp. 932 -94 1.

101-16 Strandbcrg, C. H., 1966, "Water Quality Analysis," Photogramnnzet-nrc Engineering, Vol. 32, No. 2, pp. 2.34-250.

101-17 Swanson, L. W., 1960, "Photogrammeric Surveys for NauticalCharting," Photogrammetric Engineerhig, Vol. 26, No. 1, pp.

137-141.

101-18 Swanson, L. W., 1964, "Aerial Photography and Photogrammetryin the Coast and Geodetic Survey," Photogrammetric Engineering,Vol. 30, No. 5, pp. 699-726.

101-19 Tewinkel, G. C., 1963, "Water Depths from Aerial Photographs,"Photogrammetric Engineering. Vol. 29, No. 6, pp. 1037.10412 (se8also discussion of this pa Nr by van Wijk, P. E., Vol. 30, No. 4,

p. 64 7).

, ,101-24) Theurek, C., 1969, "Coior and Infrared Experimental Photographyfor Coastai Mapping," Photogrammne'ric Engineering, Vol. 25,No. 4, pp. 565-569.

101-20 U. S. Navy Departinent (no dae), "Underwater Depth Determina-tion," Report 46, Photo Interpretation Center, Division of NavalIntelligenre, Office of the Chief of Naval Operations.

101-21 V\,ry, IN. I-., 1969, Riemote Sensing by Aerial Color Photographyfor \\'at'r lDepth Penetration and Ocean Bottom Detail," Proceed-ings Sixth Syniposium on Remote Sensing of l,'nvironment, Uni-",ersit. of Michigan, pp. 1045-1059.

101.-22 Yost, E., and \ctndt-roth, S., 1968, "Coastal \\atvr iv,'etrationU'sing N1 ultis1pt-c r- Nhotographic TechnI'j1iques," Pro'ccding", Fifth

U 42

101-22 Symposium,on Remnote Sensing of Envirbnmeiu, University of(ent'd) Michigan, pp. 571-586.

102-1 Cameron, H. L., 1952, "Tile Measuremex! of Water Curren Veloci-ties Using Parallax Methods-" Photogramnmetric Engineering, Vol.

C i 18, No. 1, pp. 99-104.

102-2 Cameron, H. L., 1062, M'Water Current and Movement Measure-ment by Time-lapse Air Photography-an Evaluation," Photogrnm-metric Engineerilhg, Vol. 28, No. 1, pp. 154-163.

102-3 Duxbury, A. C.. 1967, "Currents at t'he Columbia River Mouth,"Photograminmetrlc Engineermig, Vol. 33, No. 3, pp. 305-312.

1024 Forrester, W. D., and Cross, C. M., 1960, "Plotting of Water Cur."rctni Patterns by Photogrammctry," Photograinmietric Engineering,Vol. 26, No. 5, pp. 726-736.

10245 (101-4)

102-6 Keller, M., 1963aj "Tidal Current Surveys by PhotogrimmetricMethods," Photograminetric Engineering, Vol. 29, No. 5, pp."824.832.

102.7 Keller, M., 1963b, "Tidal Current Surveys by PhotogrammetricMethods," Technical Bulletin 22, U. S. Coact tnd Geodetic S-ir, cy.

102.8 (101-5)

102-9 Nikitin, J. S., 1957, "The Radar Method of Sthdying Sea Current,"Aieteorologif Gidrologil. No. 4, pp. 47&50; translated from thelltusian by V. Zileus for Air Force Relcarch Division, lanscomField, ledford, Ia•.achusetts.

102.10 Orms, C.. N., 10)52, 'iver Current lData f )m Aerial Photography,"Photogpam:.-etric Engineering. Vol. 18, No. 1, pp. 96-99.

102-11 k'alon, It. U\., '968, "Preliminlary Renloth Sensing of the Dela-ware lEtuary " prepared by U. S, Geological Survey' for NASA,Intvrageny Rieport 128.

43

102-12 (101-11)

1102-13 Zaitzeff, J. B. and Sherman, J. W. III, 1968, "Oceanographic Appli-cations of Remote Sensing," Proceedings Fifth Symposium on Re-mote Sensing of Environment, University of Michigan, pp. 497-527.

103-1 American Society of Photogramnmetry, 1960, Manual of Photo-graphic Interpretation, Banta Publishing Co., Menasha, Wisconsin,

K 8 68 pp.

103-2 (101-1)

f103-3 Anson, A., 1966, "Comparative Photointerpretation from Panchro-

matic, Color and Ektachrome IR Photography," U. S. Army Engi-neer GIMRADA Report, February 1966, Fort Belvoir, Virginia.

1034 Cameron, H. L., 1964, "Radar as a Survey Instrument in HydrologyS.• and Geology," Third Symposium on Remote Sensing of Environ.

mcnt, Uriversity of Michigan, pp. 441452.

103-5 Cantrell, J., 1964, "Infrared Geology," Photogrammetric Engineer-ing, Vol. 30, No. 6, pp. 916-922.

103.6 Coawel!, R. N., 1966, "Uses and Limitations of Multispectral Re-

mote Sensing," Fourth Symposium on Remote Sensing of Environ-ment, University of Michigan, pp. 71-100.

103.7 Estei, J. E., 1966, "Some Geographical Applications of Aerial In-frared Imagery," Fourth Symposium on Remote Sensing of Envir-onment, University of Michigan, pp. 173-181.

103-b Jones, B. G., 1957, "Low-water Photography in Cobscook Bay,Maine," Phologramuietric Engineering, Vol. 23, No. 2, pp. 338.342.

103-9 Latham, J. P. and Witmer, R. E., 1957, "Comparative WavefornAnalysis of Multistnsor imagery," Photograminetric Engineering,Vol. 33, No. 7, pp. 779-786.

103.10 Link, L. E., 1969, "Capabilities of Airborne Laser Profilometer toMeasure Terrain Roughness," Proceedings Sixth Symposium on

44

K

'03.10 Remote Sensing of Fnviror.ment. University of Midtigan, pp.(eont'd) 189-196.

103-11 rjohman, S. W. and Robinove, C. J., 1964, "Phiotographic Descrip-bto:a and Appraial of Water Resources," Phorogrammetria, Vol. 19,No. 3, pp. 83-103.

103-12 Macdonald, M. C., Lewis, A. J., and Wing, R. S., 1971, "RadarMapping and Landform Analysis of Coastal Regions," GeologicalSociety of America Bulletin, Vol. 82, No. 2 , p".. 345.358.

103-13 Marshall, A., 1968, "Int'rared Colour Photography," Science Jour-"nal, Vol. 4, No. 1, pp. 45-51.

103-14 k,!Anerney, J. M., 1966, "Terrain Interpretation from Radarhnmary,' Proceedings Fourth Symposium on Remote Sensing ofEnvironment, University of Michigan, pp. 731-750.

103-15 MeBeth, F. II., 1956, "A Method of Shoreline Delineation"Photogrammetric Engineering, Vol. 22, No. 2, pp. 400-405.

"103-16 Molineux. C. E., 1965, "Multiband Spectral System for Reconnais- 3•

: ~sance," Pihotogranimetric Engineering. Vol. 3 1, No. 1, pp. 131-143. ,

103-17 Raytheon Corporation, 1965 Geoscienece Potenfials of Side-Looking Ra• ar," Automet- e Fae~ity, Alexandria, Virenia.

103-18 (101-12)

103.19 (101.13)

103.20 (101-14)

10; I'l Simpson, R. It., 1969, "APQ-97 Imagery of New England: A Geo-"- graphic Evaluation," Procceding- Sixth Symposium on Remote

Setnsitg, of Environment, Universith of Michigan, pp. 909-925.

103-22 S1.'rmihrg, !.. 1961, l), aimage Siudies from AcXria Surveys,"Photogramtnetric Engineering. Vol. 27, No. 4, pp. 63LI.644.

10t3-23 (10 1-1 7d

45

103-.24 (101.18) Swanson, L. W., 1964, "Aerial Photography and Photogrammetryin the Coast and Geodetic Survey," Photogrammetric Engineering,Vol. 30, No. 5, pp. 699-726,

103-25 Viksne, A., Liston, T. C., and Sapp, C. D., 1970, "SLAR Recon-

naieance of Panama," Photogrammetric Engineering, Vol. 36, No."3, pp. 253-259.

104 (See references for 302)

105 (se6 references for 314)

106 (See references for .13)

107.1 (103-1)

107.2 (101-1)

07-3 Dingman, S. L., Samide, H. R., Sabol, D. L., Lynch, M. J., andSlaughiter, C. W., 1971, "Hydrologic Reconnaissance of the DeltaRiver ind ;ts Drainage Basin, Alaska," Research Report 262, U. S.Army Cold Regions Research and Engineering Laboratory, Hanover,New Ilampahire, 83 pp.

' , 107 4 Ei-Ashry, M. T. ai,' Wanlem,., I-. R., 1967, "Shore Line Featuresand Their Changey." Photogramnetric Engineering. Vol. 33, No. 2;)p. 184-189.

107.5 (101 5)

107-6 Leopold, L. B., Wohman, M. J., and Miller, J. P. 1964. FluvialProcesses in Geomnnrphologv. W. Ii. Freeman and Compan), SanK Franeiswc and Iondon, 522 pp.

107-7 Pincus, 11. J., 1959, "Somne Applications of Terrestrial Photogram-,mtry to thle Stud, of Shore lbmrc," Photograminetric Engineering.Vol. 25, No. 1 pp, 75412.

46

107.8 (101-15)

107-9 Stafford, D. B., 1968, "Development and Evaluation of a Procc-dure lor Using Aerial Photographs to Conduct a Survey of Coastalt?.rosion," Report (Project ERD-28) prepared for the State of NorthiCarolina by Department of Civil Engineering, North Carolina StateUniversity, 219 pp.

S; ,,107-10 Stafford, D. B. and Longfeidtr, J., 1971, "Air Mloto Survey ofy; .•Coastal Erosion," Photogramtmetric E ngitn-ering, V 0i. 37, No. 6,

pp. 565-57Zo.

Z 108.1 (108.1)

108.2 (101-1)

108.3 Anson, A., 1968, "Developments in Aerial Color Photography forTerrain Analysis," Phiotogramm~tetric En-.iginieerinig, Vol. 34, No. 10,

pp. 1048-1057.

1084 Bauer, K. W., 1967, "Flood Plain Delineation and Mapping," Sur-veylng and Mapping, Vol. 27, No. 3, Sept. 1967, pp. 393404.

108.5 Burgess, L. C. N., 1967, "Airphoto Interpretation as an Aid inFlood Sasceptibility Determinatiowa," International Copfecence ofWater for Peace, Washington, D, C., May 1967, 16 pp.

108.6 Bu|rgess, L. C. N., 1971, "Techniques of Flood Limit De~crmina-(ion," Paper presented at meeting of Americant Society of Photo-grammefry, IMarch 1971 Washington, D. C.

108-4 Dili, II. W. Jr., 1955, 'Photointerp-eation in Flood ControlApprais••s," Photogrammntrlc Engineering. Vol. 21, No. 1, pp.112-115.

1(18-8 llumer, G1. T.. and Bird, S. J. Glen, 1)90, "Critical Terrain Anlvbis,"NPihotogrammetric Engineering. Vol. 36, No. 9, pp. 939-955.

108.9 (107-0)

-08.10 (103.14)

"•- -47

108-11 Parker, D. E., Lee, G. B., and Milfred, C. J., 1970, "Flood PlainDelineation with Pan and Color," Photogrammetric Engineering.Vol. 36, No. 10, pp. 1059-1064.

108412 (101412)

108-13 Robinove, C. J. ,.nd Sbjbitzke, H. R., 1967, "'An Airborne Multi-spectral Television System," Geological Survey Professional Paper575-D, pp. 143-146.

108-14 (101414) Schneider, W. J., 1968, "Color Photographs for Water ResourcesStudies," Photogrammnetric Engineering. Vol. 34, NO. 3, pp. 257.262.

K IU13-15 ý103-22)108-16 1thornbury, W. D., 1954, Principles of Geomorphology, John Wiley

and Sons, Inc., N. Y., 618 p.

"109.1 (103.1)

F •109-2 (101-1)

109-3 Hickman, G. D., 1969, "The Airborne Pulsed Near Blue-GrecenLaser: A New Oceanographc Remote Sensing Device," Proceed.ings Sixth Symposium on Remote Sensing of E"vironment, Uni.versity of Michigan, pp. 1061-1074.

1094 (107-6)

109-5 Lukens, J. E., "Color Acrial Photograph,, for Aquatic VegetationSurveys," Procrcding6 Fiftp Sy posium on Remote Ren.ing ofEnvironment, University of Michigan, pp. 441446.

109.6 Pettijohn, F. J., 1957, Sedihentary Rocks, second edition, ilarper

0~ -and Bwotherz;, 7118 pp.

t 109.7 (1011.16)

S100)41 (102-13)

+-+ 48

+y+

110 (See references for 101 and 314)

111-1 (103-1)

"111-2 (101.1)

111-3 Aukland, J. C., Caruso, P. J., -nd Conway, W. H., 1969a, "Remote 40 jýý, Sensing of the Sea Condition wvith Microwave Radiometer Sys.ems."

Proceedings of Sixth Symposium on Remote Sensing of Environ-ment, University of Michigan, pp. 709-719.

1114 Aukland, J. C., Conway, W. H., and Sanders, N., 1969b, "Di-tection

of Oil Slick Pollution on Water Surfaces with Microwave Radione-ter Systems," Proceedings Sixth Symposium on Remote Sensing of

C-1.o Enmronment, University of Michigan, pp. 789-796.

111.5 Berherian, G. A., Oshiver. A. !H., Clark, J., and Stone, Rt., 1964,"Factors in Measurement of Absolute Sea Surface Temperature byInfrared Radiometers," Proceedings Third Symposium on Remw, teSensing oi Environment, University of Michigan, pp. 737-762.

111-6 Campbell, W. j , 1968, "Synoptic Temperature Measurements of aGlacier Lake and its Environment," NASA Interagency Report 107,February, 1968.

0

111-7 Clarke, G. L., Ewing, G. C., and Lorcnzen, L. J., 1961), "RemoteMeasurement of Ocean Color as an Index of Biological Productivity,"Proceedings Sixth International Symposium on Remote Sensing of1"ti.vironient, Univertity of Michigan, pp. 991-1001.

111.8 (1074)

111-9 (103.7)

111.10 EstcJ. E'. aind (;olonb, It.. 1970. "Monitorinig lEnvironmentalPollution," Journal of Re'note Sensing. Vol. 1 No. 2, pp. 8-13.

111-11 ;rost,,tman, R. L., Bean, i,. R., ,and Marlalt, \\. E., 1969. "Airhornenhfrared 1tadioleter lntiZati!)n otf 1%ater Surface ri-nmpnraiinre

with and ti ithout aln Elpolration-relardling Mtmio-ignlcular Laj cr7

|1)

I

111-11 rJournal of Geophysical Research, Vol. 74., No. 10, May 15, 1969,(cont'd) pp. 2471-2476.

111-12 Guinard, N. W. and Purves, 1970, "The Remote Sensing oi OilSlicks by Radar," Naval Research Laboratory Report (AD-709982)

1 11 1 June, 1970,34 pp.

1'!1-13 (03-11)

111-14 Lowe, D., and Hasell, P. G., 1969, "Multispectral Sensing of OilPollution," Sixth Symposium on Remote Sensing of Environment,Univcrsity of Michigan, pp. 755-765.

111-15 Paulson, R. W., 1968, "Preliminary Remote Sensing of the Dela-ware Estuary," prepared by U. S. Geological Survey for NASA,H,•., Interagency Rcport 123.

111-16 (101-12'

111-17 Schcrz, J. P., Graff, D. R., and Boyle, W. C., 1969, "PhotographicCharacteristics of Water Pollution," Phologrommeiric Engineering,Vol. 35, No. 1, pp. 3843.

• ii I8a(101-14)

111-19 Stingdin, R. W. and Fislc r, W., 1967, "Advancumcnts in Airborneo Infrared Imaging Techniques in Ilydrobiological Studies," Proceed-

ings, Third Annual Americin Water Resources Conference, Novem-ber, 1967, pp. 466471.

111.20 Strandberg, C. -I., 1963, "A talysis of Thermal Pollution from theo. Air," Phologrammetric Engineeding. Vol. 24, No. 4, pp. 656.671.

111-21 Strandberg, C. If., 1964, "An Aerial Water QualitN iteconiaussauet,Syste'ni," Photogranmnetric Engineering. Vol. 30, No. 1. pp. 46-54.

111-22 (101-16)

111-23 V ul Lopik, J. R., lPre,sman, A. E., and ludlum, It. L., 1968, "-,hap.ping !'olnioii with Infrmcd," Photograminictrt' Engineerinig, Vol.3-4, No. 6, pt. 561-?4.

504,

"111-24 Wesley, J., and Burgess, F. J., 1970, "Ocean Outfall Dispersion,"Photogrammetric Engineering, Vol. 36, No. 12, pp. 1241-1252.

111-25 Yost, E. F., and VYenderoth, S., 1967, "Multispectral Color AerialPhotography," Photogranmetrlc Engineering, Vol. 33, No. 9, pp.1020-1033.

111-26 (101-22) Yost, E. and Wenderoth, S., 1968, "Coastal Water PenetrationUsing Multispectral Photographic Techniques," Proceedings FifthSymposium on Remote Sensing of Environment, University ofMichigan, pp. 571.586.

112-1 (103-1)

112-2 (101-1)

112.3 (102.3)

1124 Lee, K., 1969, "Infrared Exploration for Shoreline Sprins." Pro.* ceeding. 3ixth Symposi,;nm on Remote Se..ir-g ef Environment,

University of Michigan, pp. 1075-1087.

112.5 (103-15)

112.6 (111-15)

112-7 Pearcy, W. and Mueller, J., 1969, "Upwciling Columbia River

Plume and Albacore Tuna," Procecdingu of Symposium on RemoteSensing of Environment, University of Michiganl, pp. 1075-1087.

112-8 Pestrong, R., 1969, "Multiband Photos for a Tidal Marsh," Photo-grannmetrie Engineering, Vol. 35, No. 5, pp. 453472.

112-9 Schneider, W. J., 1966, "Water Resources in the l.Verglades,"Phowogrammetric Engineering, Vol. 32, No. 6, pp. 958-965.

112-10 (101-14) Schneider, W. J., 1968, "Color Photographs foi Water Resourt.S" tuies, Photogrammetric Engineering, Vol. 34, No. 3, pp. 257.262.

51

0- - ~r, ... .. • -=. •

112-11 Snavely, P. D., Jr., and MacLeod, N. S., 1968, "Preliminary Evalua-tion of Infrared and Radar Imagery, Washington and Oregon Coasts,"NASA Interagency Report 124, prepared by the Geological Survey.

112-12 Taylor, J. L. and Stingelin,, IL. W., 1969, "Infrared Imaging forWater Resource Studies," Journal of the Hydraulic Division, Pro.ccedings of American Society of Civil Engineers, Vol. 95, January,1969, pp. 175-189.

112.13 (111-23)

112-14 Wiesnct, D. R. and Cotton, J. E., 1967, "Use of infrared Imageryin Circulation Studies o;f the Merrimack River Estuary, Massachd-setts," NASA Technical Lett•r, 78.



"115-1 Adey, A. W., 1970, "A Survey of Sea-Ice Thickness MeasuringTcehnfiqucs," Report CRC-1214, 28 p. Communication Research

-.o Center, Department of Communications, Ottawa, Ontario, Canada.

115.2 Anderson, V. !I., 1966, "lligh Altitude Side-looking Radar Imagesof Sea Ice in the Arctic," Proceedings Fourth Symposium on Re-mote Sensing of Environment (April 1966), University of Michigan,pp. 845-857.

115.3 Anderson, V. H., 1970, '"Sea Ice Presstre Ridge Study, Air PhotoAnalysis," Phoiogrannimetria, Vol. 26, No. 5/6, pp. 201-229.

115-4 Bader, Henri. 1961. "The Griland !- .... shct_" I-, V. 3.

Army Cold Jhgion• Researrch and Engineering Laboratory, Htan.over, N. i1.

115 - Bcatty, F. D., et a!., 1965, "GCeocience Potentials of Side-lookingRadar," Autometric Facility, Raytheon Corp., Alexandria, ,'irginia,'Contract I),.44.009.AM. 10,0M, fur Corps )f Engineers (in two

52

-€- 5;-

-- N- . . L

115-6 Biache, A., Bay, C. A., and Bradie, R., 1971, "Remote Sensing ofthe Arctic Ice Environment," Proceedings Seventh Symposium onRemote Sensing of Environment, University of Michigan.

115-7 Bradie, R. A., 1967, "SLAR Imagery for Sea Ice Studies,". Photo-groametric Engineering, Vol. 33, No. 7, pp. 763-766.

115-8 Cameron, H. L., 1964, "Ice-cover Surveys in the Gulf of St. Law-rence by Radar," Photogrammetnc Engineering, Vol. 30, No. 5,pp. 833-842.

115-9 Canadian Department Transport, 1965, "MANICE-Manual ofStandard Procedures and Practices for Ice Reconnaissance," Deptof Transport, Meteorological Branch, Toronto, Ontario, Canada.

"115-10 Carey, Kevin, 1971, "Icings," Monograph CRSE Ill - D3, U. S.Army Cold Regions Research and Engineering Laboratory,"Hanover, N. I1.

115-11 Edgerton, A. T. and Trexier, D. T., 1969, "Oceanographic Appli-K cations of Remote Sensing with Passic Microwave Tedcniques,"

Proceedings Sixth Symposium on Remote Sensing of Environment,University of Michigan, pp. 767-788.

115-12 Guinard, N. W., 1969, "The Remote Sensing of the Sea and SeaS Ice," Proceedings Sixth Symposium on Remote Sensing of Envir-

onment, University of Michigan, pp. 737-754.

115-13 llarwood, T. A., 1969, "Remote Sensing of Ice in Navigable Waters,"•;•'Proceedings of the Ice Seminar, Canadian Institute of Mining and

INMetcorology, Special Volume 10, pp. 95-104.

.I i5-14 Hlorvath, R., vnd Lowe, D. S., 1968, "Multispectral Survey in theAlaska Art tic," Procccdinp Fifth Symposium on Remote Sensingof Ftnvironment. University of Michigan, pp. 483.496.

115.15 Ketchum, R. I)., Jr. and Wittman, W. I., 1966, "Infrared Scanningof the Arctic Pack Ice," Proceedings Fourth Symposium on RemoteScnsiv' of Fnvironment, Univers.it. of Michigan, pp. 635.656.

115-16 Larrowe, B. T., Innet, It. B., Itendleman, R. A., and Porcello, L. J.,19 71 , ",ake-ict, Surveillance via Airborne Radar: Some lXperimental

"553

115 16 Results," Proceedings Seventh Symposium on Remote Sensing of(cont'd) Environment, University of Michigan.

115-17 Mardon, A., 1964, "Applications of Microwave Radiometers toOceanegraphic Measurements," Third Symposium on RemoteSensing of Environment, University of Michigan, pp. 763-780.

115-18 Maykut, G. A. and Untersteiner, N., 1971, "Sonme Results frow. aTime-dependent Thermodynamic Model of Sea Ice," Journal ofGeophysical Research., Vol. 7C, No. 6, Feb. 20, 1971, pp. 1550-1575.

- 115.19 MceIntosh, J. A., 1970, "A Technique for Obtaining Sea-ice Thick.-ness Measurements from Aircraft," Phpcr presented at Seminar onThickness Measurements of Floating Ice by Remolte Sensing,Ottawa, Ontario, Canada, Oct. 1970.

115S-20 MNeLerran, J. Ii., 1964a, "Infrared Sea Ice Reconnaissance,"' ThirdSymposium onl Remote Sensing of Environment, University ofMichigan, pp. 789-799.

115-21 McLcrran, J1. III., 1964b, "Airborne Crevasbe Detection," ThirdSymposium onl Remote Sensing of Environment, U~niversity ofMichigan, pp. 801-802.

115-22 MeLerran, J1. If., 1967, "Infrared Thermial Sensing," PhotogrammeericEngineering, Vol. 33, No, 5, pp. 5,17-512.

115-23 Melyer, NI. If., 1966, "Remote Sensing of Ice and Snow Thickness,"Proceedings of the Fourth Sympo.,ium on Remote Sensing of Ell-vironinent, University of Michigran.

115-24 Mlicbel, B~ernard, 1971, "Winter liegime of Rivers and Lakes,"Science and i'tigincering Monogntphy 11 1-BIA, U. S. Army ColdRegions Rtesearch and Engineering Laboratory, Hanover, N. Ii.

III

"115-25 iller, C. ID., 1962, "Ani Airborne Spectral adionemter," SecndinSN mposium on Remote Sen(ing ofd Environment, Universito of""ichigan, pp. 359-373.

:o •115-26 Portkt, I. A., I97 UnterteinrN., o 1 A o iroisave Radio-imetri- D nata." Filal eport, C ontradl N S- 11685, Raoiou etrin

Technolopy, IRn., Cambridge, Noa.6, Febr.ary 1970, pp. 1516.

• 15-1 MlntshJ.A.,197, A Tchnqu fo ObaiingSeaic Thck

r -,n. esrmnsfo icat, ae rsne tSmnro

115-27 Porter, R. A. and Florence, E. T., 1969, "A Feasibility Study ofMicrowave Radiometric Remote Scnsin," NASA Contnact NAS12-629, Electronics Research Center, Cambridge, Mass., January29,1969, p. 294.

115-28 Poulin, A. 0., (in preparation), "On the Thermal Nature of Snow-Covered Arctic Terrain as Related to Infrared Sensing," DoctoralDissertation, McGill University, Montreal, Quebec, Canada.

115-29 Poulin, A. 0., 1965, "Infrared Aerial Reconnaissance in the Ardic(Spring Condition)," Research Report 194, U. S. Army Cold Re-gions Research and Engineering Laboratory, Hanover, N. H. (Con-fidential but in process of being declassified).

116-1 (103.1)116-2 (101-1.)

P A 116-3 Fischer, W. A., Davis, D. A., and Sousa, T. M., 1966, "FreshwaterSprings of llawaii from Infrared Inages," Geological Survey,Hydrologic Investigation Atlas 218.

4 1164 Lee, K., 1968, "Infrared Exploration for Coastal and Shoreline

Springs," Technical Report 68-1, Stanford University, RemoteSensing Laboratory, 68 pp.

116.5 (1124)

116.6 (115-22)

SK 116-7 McLerran, J. H. and Morgan, J. 0., 1965, "Thermal Mapping ofYellowstone National Park," Proceedhigs Third Symposium on Re-mote Sensing of Environment, University of Michigan, pp. 517.530.

sin gap.5750

116-8 Miller, L. D., 1966, "Location of Anomalously Hlot Earth with In-frared Imegcry in Yellowstone National Park," Procredingn, FourfltSymposium on Remote Scnsirg of Environment, Univrsity ofMichigan, pp. 751-769.

%t 116.9 (103-16)

55

'C"-

__________ -,

116-10 Moxham, B. M., Greene, G. W., Friedman, J. D., and Gawarecki,S. J., 1967, "Infrared Imagery and Radiometry Summary Report,"

NASA Interagency Report 105, prepared by the Geological Survey.

Z

116-11 Pratt, W. P., 1968, "Infrared Imagery of Lordsburg-Silver City Area,New Mexico," NASA Interagency Report 71, prepared by the Geo.K logical Survey.

S- 116-12 Robinove, C. J., 1965, "Infrared Photography and Im agery inWater Resources Researdc," Journal of the American Water WoiksAssociation, Voi. 57, No. 7, pp. 834-840.

•• ,• 116-20 (101-12)

116-14 (112-11)

"116-15 Stingelin, R. W., 1968, "An Application of Infrared Remote Sens-ing to Ecological Studies: Bear Meadows Bog, Pennsylvania," Pro-ceedings Fifth Symposium on Remote Sensing of Environment,University of Michigan, pp. 435438.

116-16 Wood, C. R., "Evidence of Groundwater Flow into the LehighRiver, Pennsylvania," Paper presented at meeting of AmericanSociety of Photogrammetry, March 1971, Washington, D. C.


118-1 Kolipinski, NI. C., liger, A. L., Thomsom, N. S., and Thomsom,F. J., 1969, "Inventory of Hydrobiological Features using.Auto.nmatically Processed Multihpectral Data," Proceedings Sixth Inter.national Synmposium on Remote Sensing of Envirowment, Universityof Midhigan, pp. 79-95.

118-2 Latham, J. P., and Wittier, R. E., 1967, "Comparative WaveformAnalysis of Multisensor Inagcry," Photogrammetric Engineering,Vol. 33, No. 7, pp. 779486.

118.3 (116.8)

118-4 (11241)

56

-I I 4

.. 118-5112-9) "¶ !I I._

118-6 Smith, J. T., 1963; "Color: ,a New Dimension in Photogrammetry,"Photograpnmetric Engineering, Vol. 29, No. 6, pp. 999-1013.

118-7 Takaakzu, M., and Moraonitbhi, N:, 1960,. "On the Study and Ap-plication of Infrared Aerial Photography," Report :f IndustrialScience, Vol. 10, No. 1, University of Tokyo.

¶ 119 (See references for, 118)

120-1 Adams, W. M. and Lepley' L. K., 1971, "Audiomagnetotlunric.-,' "Journal of Remote Senslng, Vol. 2, No. 1, pp. 8L12.

"120.2 (103-1)

120-3 (101-1) o

1204 Barringer, H. R.? 1966, "The Use of Multi-parameter Remote Sen-sors as an Important New Tool for Mineral and Water ResourceEvaluation," Proceedings of Fourth Symposium on Remote Sens.

ing of Environment, University of Michigan, pp. 31ý-325.

120.5 Barringer, A. R. and McNeil, J. D:, 1971, "EPhase TM-A New

Remote Sensing Technique for Resistivity Mapping," ProceedingsSeventh Symposium on Remote Sensing of Environment, Univer-

pity of Michigan, p. 131.

120-6 Birman, J., 1969, "Geothermal Exploration for Groundwater,"Ge'olgical Society of A mnerica Bulletin. Vol. 80, April 1969, pp.""617-630.

V10-7 Cartw right, K., 1968, "Temperature Prospectinig for Shallow Gia-

cial and Alluvial Aquifcrs in Illinois," Illinois State GeologicalSurvey Circular 433.

120.8 Chase, N1. E., 1969, "Airborne Remote Sutsiag for GroundwaterStudies. in Prairie Environments," Canadian Journal of EarthSciences, Vol. 6, No. 4 (Part 1), pp. 737-741.

57

I S A

120-9 Chikishev, A. G., Editor, 1964, "Plant Indicator, of Soils, Rocksand Subsurface Waters," Translated from the Russian by Cons&,-ants Bureau, N. Y,, 1965, pp. 176-179.

120-10 Davis, B. R., Lundien, J. R., and Williamson, A. N. Jr., 1966,"Feasibility Study of the Use of Radar to Detect Surface andGround Water," Technical Report 3-727, U. S. Army EngneerWaterways Experiment Station, Vicksburg, Miss.

120-11 (103.7)

120.12 Howe, R. H. L., 1938, "Procedures of Applying Air Photo Inter-pretation in the Location of Groundwater," PIhotogrammetrdcEngineering, Vol. 24, No. 1, pp. 3549.

120-13 Kuznetsov, V. Vý, 1962, "Usc of the Properties of the Soil Coverin the Interpretation of Groundwater on Aerial Photographs,'"

04 1 Akad. Nauk. SSSR, Moscow-Leningrad, pp. 80-89. TransatedF•-• •from the Russian for FSTC by Techtran Corp., FSTC.HT-23-393.68.

120-14 (103-11)

S120-15 Meyer, G. Ya,, 1962, "Aerial Photographic Method for StudyingGroundwater," Akad. Nauk. SSSR, Moscow-Leningrad, pp. 4-15.Translated from the Rupsian for FSTC by Techtron Corp., FSTC-HT-23479-6B.

120-16 (116-1i)

120.17 (101-14)

120-18 Wermund, 1971, "Remote Sensors for ilydrogeologie Prospectingin Arid Regions," IEEE Transactions on Geoscience Electronics,July, 1971.

120-19 Wolfe, E. W., 1968, "Geologic Evaluation of Thermal InfraredImagery, Caliente and Temblar Ranges, Southern California,"NASA Interagency Report 113, piepared by the GeologicalSurvey.

120-20 (116-16)

58

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10. Explanatory Notes for Vegetation Elements (200 Series).

a. Evaluation of the 200 Series.

201. FOREST STRUCTURE

(a) Definition: A pLysical description of a forest stand typically quantified byeither the distribution of stem-diameter classes or stem-height classeb per unit of area.

(b) Interpretation Variables: Detection of this MGI element is dependcn•t onthe Jensity of the forest canopy or on the ability of the image interpreter to view theforest floor through the canopy. If a forest is multi-storied with one of the mid-storicbmaintaining a closed canopy, then all of the vegetation below this layer woidd be invisi-he to the interpreter. Since the age of trees cannot be determined reinotely, stem diam-

Soeter or height distribution is most often used to define the structure of a given foroit."In general, an image scale of not less than 1:15,000 is required for the mid- to high-

latitude forests with larger scale, required in the more complex forests of the tropics.

(c) Remote Sensor Appliations: Aerial photography (B1) has been the moslused sensor in the past for determination of this element. Films and film/filter t-ombina-tions that provide detail within hadow are:- %ould, of coure, supply more information.Microwave altimeters and lases profilers in tombination %v ith aerial plhotographN bhouldoffer a more accurate and fiter system for determination of stem or tree.

202. AREA OF FOREST TRACTS

(a) Definition: A determination of the area covered by a forest stand.

(b) Interpretation Variables: The ad~antageb of n'ea.-suring this INIGI elementfrom rentote sens;or imagery are obvious %i hcn this mtthod it compared to tht "aboriou!,ground method. Accuracy of this method depend, on (1) .,cale of imagery, (2) topog-raphy, and (3) amount of tilt in aerial image.s. For relati~el. level terrain and imagerwith lcs" than 10 tilt, accuracy within one-third of one percent has becn reported.

2 Recommended scale., werv not available in the literature in determination of this. MGIelem,.nt; however, scales larger than 1;40,t(00. ,ould provide muitable arturat-N kL-ehl.

(c. Remote Scnzo; Applitionts: A.'rial photography (1Il) has been thl re-?g""bie wensor most often used for thil M(1; cehntnt. Color and falm, color plhotograph)have proven to be of uonstidcrablic aid in .eparating forest from other regta'lan formswhen stereo photograph) % as not aiaiilablh. K-B3and radar (1L and I) imnagt'r- ha•s Alobeen L 1'•d fuo this lethntui, bidl Ac'urac<% lehrl. .ye not available (llo~vard 1970).

""0

203. CANOPY DENSITY 4

(a) Definition: A computation of the percentage of ground area within a for-est stand occupied by the vertical projection of the tree crowns (see Figure).

(b) Interpretation Variables: Canopy density is important for two reasons:(1) it is indicative of stem density; and (2) ii could be used as a measure of the ability

110 +•of a forest to conceal military objects. Crown closure or canopy density can be citi-1 mated on images ranging in scale from 1:7,000 to 1:20,000 with a standard erro• of

estimate not greater than 10 percent (Spurr, 1960). Canopy density dcter;,i;0ation• ofdeciduous forests iticluding some tropical forests have to be made when the crowns arcin full leaf. In general, canopy density is overestimated from aerial photography andunderestimated from group i 4"iervation.

(c) Remote Sensor Applications: The remote sensor requirements for thisL element are set by the dffinition of the term, i.e., the sensor must provide a near-

vertical format. Acrial photography of types BI, C(1, D[1, and E1 are the types thatwere most often used in the past. Image scale should be nt smaller than 1:20,000.

204. VEGETATION COLORATION (RELATIVE)

(a) Definition: A qualitative determination of the color of a plant community.

(b) Interpretation Variables: Based on aailable literature in the field of re.mote sensig, exact determination of this NIGI element is not po..ible with th- nr,.-sentstate.of.the-art of remote sensing. Gourley, et al., 1968, and Ieller, 1964, Iave, how."ever, reported methods for accurately describing the many color tones present on aerialcolor films of vegetation patterns, thut the imag(- colors maN hawa li'tlc re!ation to theactual colort of the vegetation as t1iey exist on the ground.

(c) Remote Sensor Application: Color tnul;Sions and nultiband imagery are

the only remutr sensor presently available to provide this information. Whlwn moredata are a#vailable on the spectral rtsponse of thit various plailt species and assoc•ialons,then airborne spectrophotomcters may lime nmort utility.

205. LOCATION OF FIRES

(a) Definition: A deturnination of th, position and bundaic•• (if a fore.stfi;n within a forest ,,tand.

It'erinawno,l), .f I4,t, est e.i ua li k. MuAao Nr.AM I,• a a 'rudut t.. I 97 I

X', 61

"•"si (b) Interpretation Variables: The most opportune time to detect a forest fire

is in its very early stages. At this stage of its fife, the fire usually is small ard located at-o• i• or near ground level. Detection of a fire in these early stages is diffitult both from the

ground and from a remote platform, Forest canopy density, stem density, species com-position, and season of year are all factors which can limit or affect detection of fires atan early stage of growth. Once a forest fire has reached sizable proportions, a constantneed exists for instant information on the location of the fire boundaries and the ntm-K ber and location of "hot spots" within those boundaries.

(c) Remote Sensor Applications: Infrared thermal imagery (3 to 5) is able toprovide enough information to locate not only the perimeter of a forest fire but alsothe more active fire areas wihiin the perimeter. References are also available to docu.mernt the use of this type of imagery to locate satll fires scattered over a large forest

'o tract.

Since the IR detectors perform so w -Il and can provide the real-time infor-K. mation needed for location and exiunt of a fire, iL. is doubtful that other sensors will be

Lused for detecting the MGI data element in the near future.

206. AREA OF CLEARGS

(a) Definition: A measurement of the areal extent of a clearing within a forest.

(b) Interpretation Variables: Detection of this MGI depends, primarily, onthe scale and quality of the imagery. Recommended scales are not available in the liter.ature for this clement, but scales of 1 ;20,000 to 1.60,000 should provide accuracy levelssuitable for most military operations.

K (c) Remote Sensor Applications: As with most MGI elements concerned withvegetation, vertical aerial photography has been the major sensor used for collection ofthis type of data. As was stated above, the scale/size of clearing relationship has notbeen fully investigated with aerial photography nor with any of the more complex remote senboru. Detection and measurement of forest clearings should be possible byother sensors such as radar and thermal infrared.

- 207. TREE HEIGHT

(a) Definition: A determination of the height of a tree stem or bole measuredfrom the ground-line/stem intersection to the highest point of dte crown. In actual

- '- practice, it is usually either the tallest tree or the average tree height that is of import-"ance to the inilitat: (we Figure on p. 63).

62

--- CROWN DIAMETER

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"tip,(b) Interpretation Variables: Crown closure or canopy density, species com-ee •position of the foremt, season of the year (deciduous forest), accuracy of image scale,

anei image quality are the major factors that affect determinatiorn of this MGI clement.Forests with very dense cat~opies preclude visibility of the forest floor. However, such

1V 1visibility is necessary for photogrammettic measuremeut of tree height. ConiferousSforests and deciduous forests imaged during the -.on-leaf period are difficult to measure

because of the non.resolution of the top portions of their cfowns. The apparent simi-larity between dlements 207 and 201 is explained by a difference in accuracy levels.NMGI element 201 refers to canopy height-a more gross measurement than 207 (TreeHeight).

(c) Remote Sensor Applications: Of the three types of photogrammetricmethods available for the height determination, only the parallax method used by theU. S. Forest Service is considered accurate enough for MGI. Accuracies with thismethod vary with scale, but ±3-foot determinations have been reported on stereo photography imagery obtained at a scale of 1:6,000.

Other remote sensors that show promise for tree-height determination in-

elude radar, microwave altimeters, and laser profilers used in conjunction with eitheraerial photography or navigation position indicators.

208. TREE SPECIES

(a) Definition: A determination of the scientific name of individual treeswithin a forest.

(b) Interpretation Variables, Identifliation of tree species from remote iensorimagery depends on a number of factors whid) include; (1) scale and spectral responseof imagery, (2) experiere e of image interpreter, (3) spectral signature of associated spe.cies, (4) ecologic range A4 spccie:, (5) species diversity oF forest, ,mid (6) season of year.In general, species of mature trees endemic to areas of 0 • world that maintain an cx-.tenure' ng or other forest product industries cap be identified from remote sensorimagery. As an example, in the 'Onited States" and Canada most of the economically im-

: portant species can be identified from imagery. Hlowever, in the tropics where speciescomposition of the formsts are more complex, identification becomes moxe difficult,even on large-scale photographic imagery.

(c) Remote S-nsor Applications: In the past, paauhromatic and infrared paikchromatic omulsious hl;ve been widely used for dctermir•,don of thit, M(, element. In

nmore recent years, color emulsions have become very popular and have proven to beSmore useful becauw le, traiting is requirt'.1 for the image interpreter utsing this typefilm. Sonit work has been ,ported where radar (KA band) and ti:trmal infrared hale

64

h.been used for forest type or groups of associated pecies identification but not for sepa-ration of individual species. Photographic scales necessary for this MCI element varyfrom 1:2,400 to 1:15,000 depending upon species and experience or training level ofinterpreter.

S 209. TREE CROWN HEIGHT

- (a) Definition: A determination of the distance between the stem/ground-lineintersection and the first fureation or limb (see Figure on p. 63).

[ . (b) Interpretation Variables: Direct measurement of this clement from aerialimagery is not possible at the present time. The logging industry requires a somewhatsimilar measurement for wood volume determination (merchantable height), but it isdetermined from ground measurements.

K• (c) Remote Sensor Applications: As was stated in par. b, there is no directmethod to determine this MGI clement from remote sensor imagery. It is believed,

, L1-11 however, that experienced image interpreters should be able to estimate this measure-T" mcnt from aerial photography obtained at scales of greater titan 1:15,000 for certain

species.

V64> 210. TREE STEM HABIT

(a) Definition: A determination of dte growth form of an individual treeI0 :usually expressed as erect or multi-stemmed.

(b) Interpretation Variable3: Determination of this MGI clement dependsprimarily on image quality, species, and the structure of the fore.st community. Provid.ing a qualitative desmiption of the dominant plants of a community is usually not diffi-cult on high-quality imagery obtained at a sca"% of 1:10,000 or greater. Determinationof ttin habit for sub-dominant spedes, however, offers a greater challenge and dependson the interpreter's ability to identify the dominant species in the forest communityand then to supply the required data from his knowledge of the known species and its

"• • --- associate species,

(e) Remote Sensor Applications: In the past and for bome time to come, verti-cal color (C( and D1) and panchromatic aerial imagery (1Il) will be tlhe best sensors forthis MIGI clement.

65

211. TREE STEM SPACING

(a) Definition: A determination of the mean distance between a tree and itsnearest neighbor.

(b) Interpretation Variables: Trec-stem spacing can be determined from aerialimagery for those trees that form the canopy or emerge through the canopy. Sub-dominant trees and those stemb growing beneath the canopy of the individual crownsof larger trees are not imaged and, therefore, cannot be measured. Multistoried forestscommon to the tropics provide tie most difficult measurement conditions.

(c) Remote Sensor Applications: Aerial photography of types B1, C1, and D1air the sensors most often used for determination of this data element. Image qualityis probably more important than scalc when estaLlisifing sensor requirements for deter-mination of tree-stem spacing. Any emulsiun that provides detail within shadow areasand that will resolve the tree crowns would be suitable. A scale of L20,000 or greateris recommended.

0

- 212. TREE CROWN DIAMETER

°'1 (a) Definition: A determination of the average diameter of a tree crown whenviewed from a vertical posit;on (see Figure on p. 63).

(b) !nterpretation Variables: Determination of crown diameter from remote

sensor imager) requares a number of simple distaie measurements.,. The ncnurecmentsare complicated, however, by the ,mall size of the tree crown on the inmage, dense sha-dows ( iused by adjacent tree crowns, and the fact that in most canopics the ompllctcrown is not visible. Crowvn diameter is ,ne of the inore important measuremcnt6 sincefor most coniferous species and many hardwoods urowvn diameter is related directly tostein diameter and is the only method of obtaining stem diameter from R.S.I.

rt (c) Remote Sensor Applications: Aerial photography of types 131, Cl, and DISare thessenor ty pes recoismendced for this element based on work lone in the past.Photograph, obtained at a scale of 1.15,000 or larger should enable in interpreter to

Sdivide most forest ly p|'s into 2-iich stem-diameter das.w., in areas, wshen this .rc.adlom-ship is known.

213. TREE CROWN LENGTH

(a' Definition: A mna.surmnent of th, disLmve but u ecvn the low est branch ofa tree vro-%, n awl the uppetr wrmninus of the trunk or :,tcn (.re Figurv on1 p. 63).

(b) Interpretation Variables: This MGI clement is the complement of 209(tree crown height). At the present time, a direct measurement of crownr length fromremote einsor imagery is not possible except in very open forest stands where measurements may L possible using the shadow of the tree. Oblique imagery of the margins

' of timber stands will not produce reliable results because tree crowns grown underthese wnditions arc not representative of the crowns growing w ithin the torest exceptfor forests adjacent to recent clear-cut areas or wind-thrown areas.

(c) Remote Sensor Applieaii;c•: Photographic remote sensors that providedense black shadows would be suitable for this MGI data element. Sensor types BI,C1, and DI obtained at a scale of 1.1 5 ,000 or greater would provide the most accurateinformation.

214. TREE BRANCHING HABIT

(a) Definition: A determination of the branching characteristics of a treecrown, i.e., horizontal or divergent.

S.....ree(b) Interpretation Variables: The ability of an interpreter to separaie individ-ual tree crowns into the groupings listed in para. a is dependent on the following facturs.

K ty pe, scale, and quality of the image and also on the density, season of year, and speciesof tree. Fortunately, these two types of crown forms can be ahsociated with two major

• •• groups of trees-coniferous and deciduous. Conuferous tree specieb normally have huri' zuntal branching, while divergent brarfching is ubually a&sAmiatcd with deciduous bpecic,.

Infrared color and panchromatic films provide a zrrmiod of separating these majorgroups since the coniferous tpecies arc dark toned on the IR panthromatic and imagedSa deep red on IR color emulsion. While scaleks ast mall as 1.40,000 would be adequate,1.20,000 would provide more reliable information oi Urow:k hlhapC as %vcll ab branchingform.

(e) Remote Sensor Application: Panchromatic infrared and color films of"' types, 1)1 and EI offer the most ziuitable means of determining this M;G! element. Atthe preant state-of-thl-art, thari appear, to be no other sensurs which t ould provide

S~this data as well as aerial phot:ography.

S~215. FOREST UNDERSTORY DENSITY

(a) Definition: A det'rmination of tlh mnmiber of strims pler unit of area inunder-tor. of a forest. (An undt'rstorN " it, defitid at, aN %,1d% ývgctation grov.oeing belath the dominant and co-dominant tree., in a foret.)

67

(b) Interpretation Variab!=!: An exact measurement of the MGI element isnot possble from aerial imagery at the present time. Understory density has been esti-mated from oblique Fhotographs by all interpreta' having a largr amount of experiencewith actual ground conditions. Ebtimates of underbtory density have also bean accom-

4A plished by measuring canopy dens'ty (element 203) and assigning a value based on a de-crease in understory density with an increase in canopy density. Hlow ever, both meth-ods require image interpreters who are experienced not only with variations in plantcommunities but also with knowledge of forest conditions within the "rea of interest,

K ' (c) Remote Sensor Applications: Vertical aerial photograph) with panchro-matic film, unfiltered, at a scale of 1:10,000 or larger would probably be tie best re-mote sensor for thi? MGI element over dense forests. In fairly open to open stands,aerial photography in conjunction v. ith a laser profiler would provide enough informa-tion to determine understory density.

- • 216. SHRUB STRUCTURE

(a) Definition: A determination of the physical composition of a shrub standasually expressed as tie distribution of btem height or diameter. (A "shrub" in definedas a woody plant 10 feet in height or under and is usually multi.stemmed.)

00 (b) Interpretation Variables: Mcaburements for determination of shrub struc-ture from remote sensor imagery require methou-, bimilar to those used to determineforest structure (element 201). All of the factors affecting measurement of forest

Sstructure are also common to ihrtub st: ucture with the additional need of large-scaleimagery. The relationship between crow in diameter and stem diameter for shrub -'pctiC%has not been developed as yet so exact determination of this MG I element from R.S.I.

-OZ is not pouible at this time. A number of studiecs have been reported in the literature onthe use of R.S.I. for shrub height and density measurements (see element 217).

(c) Remote Semsor Applications: Aerial photography of types lII through El

K li hais been the piimary sen.ýur for deriving thits information in the past. Other sexnsors-radai, for example - hae been tritcil but have nut been ,tucce.ssful because of resolutionproblem-,,. Aerial photography obtained at the ,eales of 1.10,000 or greater is requiredfor determination of this element.

217. SHRUB DENSITY

(a) Definition: A determination of the number of shrub stem•s per unit of area.

(b) Interpretation Variables: Measurenivnt of shrub deln.zity fronm Ii.s.1 is d(t-ptlend-.lt oin the qualits, datc, and stale of thr, im,,gerr and aLo )n the d•int.! and .,lwpvi-

68,

composition of tie shrub stand. Shrub stands that arc so dense that detectin of indi-vidual crowns becomes difficult from ground inspet.:ion wouldbr impossible to mcea-sure" from R.S.I. Convermely, very small shrubs widiy spat ed may also be difficult todetect if such aids as their shadows arc not used to enhance iheir location oil the image. 4Mcasurement of the percent of area occupied by shrubs ,:an b6. a more useful term thanstems per unit of area.

(c) Remote Sensor Applications: A&, with most MGI data elements in the vege-tation category, aerial photography of types BI, Cl, DI, and El is most often used fordetection of shrub density. Thermal infrared scanner imagery and radar have aLso bcenused, but resolution is often a problem with these types of sensors.

218. SHRUB SPECIES

(a) Definition: A determination of the specific or scientific name of a shrub.

(b) Interpretation Variables: Most of the problems associated with identifica-" >,tion of tree species arc also common with identification of shrub species. In the eastern

forests of the U. S., for example, many shrub species can be classified by experiencedinterpreters using their knowledge of plant associations with known tree species andsite requirements.

(c) Remote Sensor Applications: In general, aerial photography obtained at ascale of not less than 1.15,000 is suitable for remote sensor detection of this MGI ciemcnt. Color emulsions bhuuld be conbidercd superior to panchromatic films when in-"terpreter experience of a particular location is either lacking or not well developed.

219. GRA& ý DENSITY

(a) Definition: A determination or the number of grass stem.s contained in aunit of area. When measured from ILS.I., this element is usuall) expretnied as percentof area occupied by grass rather than actual number of stems per Emit of area.

(b) Interpretation Variables: On large-scale, high-qualit) aerial photograph),it is possible to determine gra&s density (Carneggie and Reppcrt, 1969). Accurac) of"thib information, of courne, depends on the precrion of thli rc-quired photogrammntritmcasurcmcnts,. ,\n area grid template it ,imsiali emplo)ed as ,n aid to the mlaterpr,-turin determining percent of land area occupied by grass.

(c) Remote Sensor Application: Arial photograph-, iL the only tenso: f&,aiblefor determinaoiun of gias den.sity at the pres-nt time. Since color emul.,ion u.suall• pro-

'vidve the greate.st ontraAt hOemte gras-s ouminunities' of bth.V4t-, plant k,,tmuzii,-s

69

- ,f .-

and bare soil, it should be considered superior to panchromatic films for this MG! ele-ment. Recommended photographic scales vary from 1:600 to 1:1,500 for accuratedetermination of grass density.

220. GRASS SPECIES

(a) Definition: A determination of thz scientific name of individual grassplants.

(b) Interpretation Variables: Determination of the specific names of thegrasses is difficult and often requires close ground inspection of the plant with a handlens. In many instances, positive identification can only be made when the plant is inthe flower stage. (Most of the identification keys are developed arutrod characterizationof indihidual psrts of the flower.) In recent years, however, successful species recogni-tion has been accomplished using large-scale aerial color films of types C1 and DI. Inmost instances, identification of grass sptcies depende on accurate ground truth and cxperienced interpreters with a knowledge of the plant ausociations endemic to tde gco-graphical area of interest.

"the (c) Remote Sensor Application: Vertical aerial color photography has beenthe most applicable sensor for this MGI element. Scales larger than 1:10,000 are re-quired if the necessar ground truth is not available, i.e., vegetation map, groundphotography, etc.

221. AREA OF AQUATIC VEGETATION TRACTS

(a) Definition: A measurement of the areal extent of aquntic vegetation.

aqutic(b) interpretation Variables: Determination of the boundaries of an ara ofSaquatic vegdtatiun requires a remote •cni.u bstcm that will provide maximum contrabtbetween the vegetation and the water. In gencral, the infrared-sensitiwe eIuislionms (colorand pandiromatic) have this qua!;ty atd have wcen successfully utilized for this purpose.Infrared sensitive color films would probabl) offer tile maximum contrat w-,ith the .cgetation varying from d(kep-red to red and the water, from dark-blue to blue. The recogni.tion of the w4ater.'vegetation/land interfaces is often difficult but can usually be accom-plitshed under stereo viewing. Aquatic bpecies- growing tivar thiv water surface arc usuallydetektable with infrared color cmulsion, but %Nill hlietunw more difficult or imp,.,,ilhd, todctiinate in water with high turbidity.

(c) Remote Sensor Applications: S n•sors of type.,, C., 1, F, and J are appliabhlefor determiniiation of this M',l;l clement. \\hilt- inodcb ,f imagery other than .vitic~dcould be tusd, nar-vertical imag-rý wtould be mort- suitabie. Infrared color vertical

"i• 71)

/I

photography obtained at scales oT 1:10,000 or larger would provide the best sensor for-, measurement of this data element.

222., AQUATIC VEGETATION SPECIES

S, (a) Definition: Determination of the specific or scientific name of individualaquatic plants.

(b) Interpretation Variables:. Aquatic plants vary in size a•cording to specieso- mid length of growing season. in general, the portion of the plant visible to the inter-preter may range from as small as 1/8 inci in diameter to-several feet in diameter.

Detectiqn of aquatic plants depends, therefore, on size of plant or leaf area visible tothe interpreter or, in the case' of species growing entirely under water, leaf area, tur-"bidity, of the water, and depth below surface. In most instances, aquatic species formpure communities so that species recognition is not based on individual plant character.istics but rather On knowledge of habitat requirements, ground truth, and water depth.

- =(c) Remote Sensor Applications: Requirements for this element are similarto MGI element 221 with the exception of a need for a larger scale, especially withspecies that grow entirely underwater.

223. AQUATIC VEGETATION DENSITY

(a) Definition;. Determination of the number of stems or plants per unit areaK '.of any species of aquatic vegetation.

thi8 (b), Interpretation Variablesi Normally, there are two niethods for quantify.ing this element: (1) by measuring the percent of an area occupied by aquatic vegeta.tion; and (2) by counting the number of stems per unit of area. The first method

Syields a percentage, quantity rather ýhan a stem count; but, in many instances, thismeasurement is rmore useful and easier to obtain. The first method can also be cr-ployed using smaller scale and lower quality imagery than the stem-count method.

(c) Remote Sensing Applications: Color and false color emulsions are the.most ueful sensori for this element because they provide maximum contrast betweentie water and the vegetation. Scal"s as simall ab 1:40,000 can be employed, dependingon the tize of the aquatic spepies, for quantifying the MGI element.

"224. CROP SPECIES

(a) Definition: A determnimation of the specific name of an agricuilunai crop.

71

"(b) Interpretation Variables: Crop identification from R.S.I. is dependent oi.- season of year, date of imaggery, type and quality of imagery, and. to a certain extent,

image scale. Of equal importamce is a knowledge of the crops endemic to tile area ofinterest. The interpretcr knowing that tie crop he is attempting to identify can only"be one of a possible five species has a much easicr task than: ;f it were one crop out of apossible list of 20 species. The se•ce of thc imagery nece(,ssary to determine crop sptcicsis difficult to define since mapr of the studies reported in the literature indicate thatthe tone and texture of the crup image was used for identification rather than the char-acteristics of the individual plant. With the availability of spectral-r•sponse curvcs formost crop species, selection of the remote-sensing system can now be based on the"maximum separation between these curves at any frequency.

(c) Remote Sensor Applications: Color mad false color filhnl providc, the mostuseful data for crop identification at the prs.ent time. Scales as %mall as 1.40,000 used

:• . with accurate ground data have been employed for crop identification. Nlultiband

Scanners have also been used and have been proven t0 Lu highly beneficial where thecolor films provide little tonal differences between two crop species. Radar can pro-vide only broad clasrs of agricultural crops now ; but, with more study and advancesin radar technolo•.., this sensor should be, in the future, the most useful sensor for thistype of work at small scales and large area coverage.

225. CROP HEIGHT

(a) Definition: A determination of the vertical height of an agricultural crop.

ii (b) Interpretation Variables: Quantification ef crop height requires methods., •-'• •iAmilar to the mea~suremenia of grra•,,s height and 6• .etal, a photograninictrit prob-

lem. The accurat% of these measurement-s depends on ac-urcte ground control (v.erticaland horizont,d), resolving power, and calibration of the R.S.I. s)stcm. The photogram-mctrit, mcthod.s eimplo) ed for trec-height determination arc not ,:onsidrrd adequate

0'-o fur crop height ,Ance measurement error of these methods i.% usuall. larger than the! " height of the average crop.0

(c) Remote Sensor Applications: P1hotogram metric mea.surcment.s obtainedfrom stereo vertical photographk taken at sca'e., of 1:10,000 with a cartographic eam.era should provide adequate data for aeasurement of crop height. This ,. steon. how -cver, require,, a t.cumph' ground-contro; net and fir-t -order ,tcreo plotting equipment.A las•er Iprofiler ,houtd bc uscd f- r this., tI pe t)If mcasurensent once this, equipment hasbeen perfecled.

72

2-26. CROP PLAITUNG TIMEI

S(a) Definition: A determination tf the age of any given crop.

(h) Interpretation Vari Uies: Direct determination of this MGI element fromR.S.". :s, of course, impo.,isible unless the imagery is obtahied during the aciual time ofplanting. Indirect detzrmnination should be posýble, howeier, if enough ir-f- .,ltiOn isknown concerning the general agricultural practices of the area of interest. Localweathtr history and local custom determine the crop planting date- more often than4tchnical knowledge or information. The interpreter aware of local weatla- ,ditiow,and crop types should be aijk to estimate crop planting date bLy measuring .op heightat an) time during the grow irag season. Another me:hod of detecting the planting datecould be provided by requiring s£qmtzntial irmtag-ry of an area beginning in earl) bpringand ending in early summer.

(c) Renwte Sensor Applications: Aerial photography obtained at a sc.0 of1.10,000 would provide suitablk data to ascertain this MGI element if enough informa.tion of local agricultural prwceiccs were aiailable. This stasor system %Vuld also be applicable for detecting crop planting data by sequential photography.

b. References and Bibliography for the 200 Series.

201-1 Sayn-Withgenstein, L. and Aldred, A. H., 1968, "Avionics in ForestResources Inventories," Canadian Aeronautics and Space Journal,Vol. 14, No. 8.

201-2 Spurr, S. H., 1948,AeriaI Photography in Forestry. The RonaldPress, Ne, York.

201-3 ltcyi;ers, P. C., 1968, "Quantification of Vegetation Structure on"Vertical Aerial Pnotographs," Land Eraluation, Mae William ofAustralia

201-4 Howard, J. A., 1970, "Stereoscopic Profiling and thc Photogram-metric Degcription of Woody Vegetation," The A vs1rafian Geogra-phie', Vol. 11, 3 pp. 359-72.

202-1 (201.3)

202.2 (201-4)

73

V,.

V

,-Z

202-3 Howard, G. E., and Sapp, C. D., 1970, "Evaluation of SLR Imageryof Tropical Lowland Vegetation," American Society of Photogram- Imetry, Paper from 36th meeting.

1 2024 Spurr, S. H., 1960, Photogmmmetry and Photo-Interpretation,V Ror.2d Press Company, New York.

203.1 (2024)

204-1 Gourley, J., Rile, H. T., and Miles, R. D., 1968, "Automatic Tech-niques for Abstraeting Color Descriptions from Aerial Photography,"Photographic Science and Engineering, Vol. 12, pp. 27-35.

204.2 Heller, R. C., Daverspike, G. E., and Alrich, R. C., 1964, "Identifi.eea'ion of Tree Speciets on Large Scale Panchromatic and ColorAerial Photographs," U. S. Dept of Agriculture Handbook 261.

205-1 Hirsch, S. N., 1962, "Applications of Remote Sensing to ForestFire Detection and Suppre.,ion," Proceedings of the Second Sym-posium on Remote Sensing of Envirunment, Institute of Scienceand Technology, The University of Michigan.

205.2 Hirsch, S. N., 1964, "Preliminarv F- perimental Results with hnfra-r.cd Fire Scanners for Forest Fire Survei!lance," Proceedlings of theThird Sympoxium on Remote Sensiig o1 Environinent. Institute (if

Srience and Tehmoiogy, University of Nlichigan.

205-3 Hirsch, S. N., 1968, "Project Fire Scan- Summn• of 5 Yvars'Proerer.s in Airborne Infrared Fire Detection," P:oceevding. of theFifth Symposium ol lRemot," slen-ing of Enlvilnment, il.t4ititvof Science and Technology, University of Michigan.

_206 1 Cariwggic, 1). N11. Lat leu'r, I). 1",_ 1966, "'1. Of ` tiltlibad Re.V44 inute St-risiig in Fore.,t aod lKange h,.entor% ." Ph/wU ,gr'mnin tria.

"V o.. 21, pp.1! 5-1-11.

_21 2 (2i)2- t)

L7J"

4

206.3 Tamoasegovic, Z., 1968, "Direct Determirixion of Area nistrLhu-tion Based Upen Topographic Features by Means of the Wid B94Aviograph," Photogrammetria, Vol. 23, No. 4

2064 TM 30-245, , 967, Image Interpretation Handbook, Reconnaissanceand Technical SuppotL Center, Naval Air Systems Command.

207-1 Aldred, A. H. and Kippen, F. W., 1967, "Plot Volumes from Large-Suale 70mm Air Photographs," Forest Science, Vol. 13, No. 4. .4

207-2 Avery, G. and Myhre, D., 1959, "Composite Aerial Volume Tablefor Southein Arkansas," Southern Forest Experiment StationOccasional Paper 172.. .

207-3 Johnson, E. WV., 1958, "Effect of Scale on Precision of IndividualTree tlegipt Measurements," Photogramnmelric Engineering, VAo.24, pp. 124-.15 .

2074 Katz, A. i1., 1952, " h1, c Measurements with the StereopticContinuous Strip Camera," Photograminetric Engineering. Vol. 18.

207-5 Kippen, F. W. and Sayn-Witfganstein, L., 1944, "Tree Measurementon Large tcale, Vertical, 700mm Air Photographs," Canadian D)eptof Forestry Publkation No. 1053.

207-6 Lons, C. 4l., 19b7, "Forest Sampling with 70amm Fixed Air-Baei'hotographyv from th'licopters," Photograuinmetria. Vol. 22, No. 6.

207-7 1.vons, E. &., 195 % "Nleasurement of Vertical tlcights from Sigle"('.bitmu Aerial Plhotographts," Photogramnmetric Enginecfmig, Vol.23. No. 5.

2017-0 (;erratl, 1). j., 9b9, "1Frror Propagation in Km.ti g l ree 8i..2Pwholgrwnietri,- EtrIginering. Vol. 25, No. 4..

90-9,9 Pojw. R. B., 1957, "11T Effc't .of '•hoto Salh on the k\cura.ve of1-oret4 Mleasurement,'" Photogramiintric Eng'ieeriog. N ol. 23. No.'. p11 869.873.

7 ,- 1? (20l 1 11

207-11 Smith, D. C., 1969, "Timf. Volume with a Kelsh Plotter," Photo-graminmetric Engineering, V ol. 25, No. 4.

207-•i2 Westby, R. L., Aldred, A. H., and Sayn-Wittgenstein, L., 1968,"The Potential of Large-ScAle Air Photographs and Radar Altime-try in Land Evaluation," Land Evaluation, MacMillian of Australia.

207-13 Worley, D. P. and Landis, G. H., 1954, "The Accuracy of HeightMeasurements with Parallax Instruments on 1:12,000 Photograph.9,"PPhotogranmnietric Engineering, Vol. 20, No. 5, pp. 823-829.

208-1 Avery, G., 1960, "Identifying Southern Forest Types on Aeri,Photographs," Southeast Forest Experiment Station Paper No. 12.

208.2 (206.1)

208.3 Hoack, P. M., 1962, "Evaluating Color, Infrared and PanchromaticAerial Photos for the Foreqt Survey of Interior Alaska," Photo-graminetric Engineering, Vol. 24 (4).

2084 lHeller, R. C., Doverspike, and Aldrich, R. C., 1964, "Identificationof Tree Species on Large-Scale Panchromatic and Color AerialPhotographs," USDA Agriculture Handbook No. 261.

208.5 Johnson, P ! x,;,d Vogel, T. C., 1966, "Vegetation of the YukonFlats Region Alaska," USACRREL Researel Report 209.

208.6 Joyce, A. T., 1967, "Aerial Photographic Interpretation of Tropi.cal Vegetation in Costa Rica," M. S. Thesis. Pennsylvania StateUniversity, School of Forest Reources.

208.7 Northop, K. G. and Johnson, E. W., 1970, "Forest Cover TyreIdentification," Phoiograinmetric Engineering, k, ol 3C (5).

208-8 Perry, J. T., Cowan, \\. R., and lleginbultom, 1l. lH., 1969. "Colorfor Coniferous i,'orest Species," Piotogrammetric Engineering.Vol. 23 (5), pp. 861ý 873.

208-9 Sayiv-Wittgenstein, LI., 1961, .... t,,tion of Tree Species on AirPhottographs by Crown ('Dea .ciiK, lhpt of Foreýstry, Canada,Tt'chnical No(t No. 104.

o 208-10 Ste!lingwerf, 1969, "Interpretation of Tree Species and Mixtures"on Aerial Photographs," Biogeographic, Vol. 4, No. 2, pp. 83-91.

208.11 (207-5)

208-12 Miller, It. G., 1960, "The Interpretation of Tropical Vegetationand Crops on Aerial Photographs," Photograrnmetriu, Vol. 16 (3).

208-13 Meyer, M. P. and Erickson, V. G., 1964, "Relationships of AerialPhoto Measurements to the Stand Diameter Classes of a MinnesotaHardwood Forest," Photogrammetric Engineering, Vol. 30 (1).

208.14 Losce, S. T. B., "Photographic Tone in Forest Interpretation,"Phom'ogrammetric Engineering. Vol. 17 (5).

208.15 Truesdill, P. E., 1959, "Study of Vegetation and Tcrrain Conditionsfrom Aerial Photography," Final Report on, Bureau of AeronauticsProj,;ct 'T'E)D PIC, 11114747.4.

208-16 Wickens, G. E., 1966, "The Practical Application of Aerial Photog.raphy for Ecological Surveys In the Savannah Regions of Africa,"Pbotogrammetrla. V'ol. 21.

208-17 Zsilinszkv, V. G., 1964, "The l'ractive of Photo Interpretation fora Forest Inivemlory." PIotogratnmietria. Vol. 19.

209 There are no rfererncc. auailahdl for thisN M;I element.

"210-1 Avery, G., 19611, "lEvaluating Understory Plant Cover From Aerial0 Photography," Southern Fort E'prinj%.iit StationU. S. Forest

2 10.2 Aldrich, It. C., 196, "l"-,ortrk \lXlli,'ationm.- of 70 mm Color,",'Phollforamtnetric 'tngingecrtng. Nl. :12. No. 5, pp. ,,1.6.

$' 0'• 2!!211 - \htw.-i-,r, K. E-.. 190(. '"'ramiing H ladlbook: lBa.j 'l'echnituc'., In

Frl"rst lPhoto lut rprt~ u mn.' [ . S. Forlst ScruCr.

0

L 211-2 Avery, G., 1966, "Foresters Guide to Aerial Photo Interpretation,

Agricultural," Handbook 38, USDA Forest Service.

Su 211-3 (207-6)9

9

212-1 (207-5)

o •212-2 (207-6)

212-3 Minor, G. 0., 1960, "Estimating Tree Diameters of Arizona Ponde-"rosa Pine from Aerial Photographs," Research Note 46, RockyMountain Forest and Range Experiment Station-US Forest Scrvicc.

212-4 Sayn-Wittgenstein, L. and Aldred, A. H., 1969, "A Forest Iaventoryby Large-Scale Aerial Photography," Forest Managtment Institute,

2 5Canadian Forestry Service.

212-5 Willingham. J. W., 1957, "The Indirect Determination of Forest

Stand Variables from Vertical Aerial Photographs," Photogram-K metric Engineering, Vol. 23, No. 5, pp. 892.894.

213 No reference available.

214.1 (207-6)

214-2 (207-9)

214-3 Willingham, J. W., 1957, "The Indirect Determinatioit of ForestStand Variables from Vertical Aerial Photograph,," Photogram-

rmetric Engineering, Vol. 23, No. 5, pp. 892-894.

215.1 (210-1)

S. 215-2 Swantje, 1I., 1957, "Photogranmctric Methods tn l eforestaton"Survey,-,," Photograminetric Engineering. Vol. 23, No. 4, pp. 789.790.

:15-.3 (201-3)

,.. 78

216-1 (207-1)

216-2 Anderson, H. F., 1956, "Use of Twin Low-Cbliquc Aerial Photo-graphe for Forest Inventories in Southeast Alaska," Photogram-metric Engineering, December, pp, 930-934.

216-3 Stellingwerf, D. A., 1968, "Practical Applications of Aerial Photo-graphs in Forestry and Other Vegetation Studies," InternationalInshtutc for Aerial Survey and Earth Sciencer.

217 See MGI element 216 for references.

218-1 Peeking, R. W., 1959, "Forestry ApplicationE of Aerial Color Pho-Stography," Photogrammetri Engineering, Vol. 25, No 4, pp.559-565.

218-2 Carneggie, D. M., and Rcppert, J. M., 1969, "Large Scale 70 inmAerial Color Photography," Phologrammetric Engineering, Vol

o 25, No. 3, pp. 249-257.

0

219.1 (218.2)

219-2 (206-1)

220-1 Becking, P. W., 1959, "Forestry Applications of Aerial Color Pito-tography," Photogrammtrirk Engineering, Vol. 25, No. 4, pp.

10. 559-565.

220-21 ("218-2))

220-3 Carne.gic., D. M., 1968, "Remote Sensing Applications in Forestry,"Analysis of Remote. Sesing bala for Range Rewurce Management,A nnual Progress keport, N ASA.CR. 100894.

220-4 Sayn-Wittgczn.,tl L., 1961, "Pheiulogical Aids to Swerier. Identi-fieation on Air Phot,,graphii," l)ept of lForstr%, Canada, Tech.

"- •Note No. 104.

>xi, <

-(-4

221-1 Kolipinski, P•. C., and Hliger, k. L., 1967, "Panchromatic AerialPhotography in Hydrobiological Research," Proceedings of Work-"shop, Infrared Color Photography, In the Plant Sciences, FloridaDept of Agriculture.

221-2 Pestrong, R., 1969, "Multiband Photos for a Tidal Marsh," Photo-gramnmetri: Engineering, Vol. 25, No. 5. 4

221.3 Strandberg, C. H., 1967, Paper presented at Workshop, Infrared"Color Photography, In the Plant Sciences, Florida Dept of

So ,ncultue.

2214 Welch, R. 1., 1970, "The Use of Color Aerial Photography In

Water Resource Management," Earth Satellite Corp., Berkeley,California.

0 222 See references under element 221.

r *° 223 See references under clement 221.

224-1 lioffer, R. Al., 1967, "Ihterpretation of Remote MuhispectralImagery of Agricultural Crops," Purdue University of AgriculturalExperiment Station, Research Bulletin, No. 381.

C,,

224.2 Goodman, NI. S., 1959, "A Technique for the Identification ofFarm Crops on Aerial Photographs," Photogrammetric Engineer-

ing, Vol. 25, No. 1, pp. 4449.

) 224.• Dill, 1I. W., 1959, "Use of dhe Comparison Method in Agri.maauralAirphoto Interpretation," Philogrameaic Engineering, Vol. 25,

o No. 1, pp. 4449.

2244 Sinionett, 1). S., Eagleman, J. E,., and Erhart, A. B., 1967, "Tht.Potential of Radar as a Remote Sensor in Agriculture: 1. A StudySWith K-Band Imagery In Western Kan.as,, T'lv U;uversitv of Kan.sas, Center for Re.arch, Inc., Report No. 61-21.

0

¢80

225-1 Buckmeier, F. J., 1970 "An Evaluation of Airborne Sensors for

Site Selection Engineering Data Requirements," Tech Report No.AFWL-TR-69-95,, Air Force Weapons Laboratory, Air Feizee Sys-tems Command, Kirtland Air Force Base, New Mexico.

225.2 (201-3)

225-3 (201-2)

q<> 226 No rcferenc for this element.

141

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41

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I ?- 4 11. Explanatory Notes for Landforms and Surficial Materials Elements (30M)SeriE4.,)

a. Evaluation of the 300 Seaies.

301. TYPE OF SURFICIAL DEPOSI

(a) Defihiition: A determination of the type of surficial deposit based onorigin, occurrence, and cniviroinmertal setting.

(b) Interpretation Variaibles: This discussion will emphasize the -.ye ;dentifi-cation, thraugh recognition of primary characteristics, of the unconsolidated surficia!

materials, or deposits, overlying the bzcdrock of a region. Surficial geologyi tcr;isomnetime~s used for these deposit. as opposed to bedrock geology Which IIPAIQ pnlmtsii y'with the consolidated vocks and sediments of the upper part of the carth*s cru.". I'hcproperties of thesc bedh ock units, where the bedrock is exposed in outcrops, can be dt--termined anid the rock type can be identified in much the same manner ai surface de-posits are identifietd. The bedrock units have distinct proparties and outcrop expression.Bedrock untit.. are the parent materials from which- the surface deposits wecre originallyderived. This relationship is most apparent for deposits formed in place. The surfacedeposits have accumulated anid undergone change through the action of various geol-~6icprocesses, anid they occur in association with (or comprise) characteristic landformssuch as floodplains, terraces, alluvial fins, glaclai moraines, etc.

Geologically, surface deposits afe classified anid their distributions mappedaccordinig to similarity of physical properties and relation to landforms wvith some at-

(4 ~tenition paid tv origini and genetif- relationships. Engineering soils classifications are ap-pliLd to surface depositts largely on a physical brbis, with pprameters such as size di'stri-but ion, clay contcnt, and engineering behavior of the m~aterials emphasized. Geneticrelationshiips, are not con~sidered. These engineering properties- can be determtined di-r'det) on the ground bv sampling, or tlreý can be tsiimateA (or predicted) using variousty pes of -,t isor imagery. The remote dutermninatittn of properties of curricial depositscant be made itith greater assurance if the type of d.zposit cart be po)sitively identified.ft Based onl knovvledge of the probable origin and characteristicts common to a particularh pe of deposit, addi'tional inforeties: cart be made or. such properties as, texture, com-Positi-ni, probable depth (if not directly observable), etc. These inferewecs vvill b~emadle vi ith regard to posible', mRnoifiatioiis in pro 1 )crtiets brought about by the cenAironl-mental settinig in, which the tit-posit occurs.

This dliscussionk of surface mnaterials and( de1 )osit- dloe,, not includo- soils die-Iermixnatiozi, in the agri~ nittral or pcdoiogit al sen~se. Suich sois ta-ificationsarc con-cernted primarilk with thome surfai-e anid niear-,surface- horizons de 1-coped in earth

materials where vigorous biological activity occurs and where rootkd planwts are support-ed. Pedological. soils classificaticnls do, hBwever-, include cansiderations if morphologyand landform association. Surficial deposits derived fromn bedr-iek units can be forumdin place under the influence of various physical and chemicai processes, or they can re-ýult from erositii aad subsequent dzrnosition by various transpoi ting agents such as win]1,water, ice, and gravity -or combinations of these. Transport can occur over short dist-ances~ only, ae in the case of slope coliuvium, or transport mayý be over grerat distancesas in thejcase of some loess deposits. Primary relationships between a deposit arnd its

ý7source area afe generally more evident where transport dibian..-eb are of small magntude.The esutantdepsiteiter alaidfor inits wn ightor ssocate wit a isic

lar. form, has certain characteristics which ind'.1ate its prirziary mode of origin. Sand

dunes, for instane, accumulate under the influence of winds; glacial eskers and out-wash d~posits are products of glaciers and melitwater from glaciers.

Numerous clues are used !o initially lIiscriminatc and subsequently identifya deposit and to determine- its proFerties from ;cmotc sensor imagery. These includecolor (.ir grey tone), size and, Phapt. of deposit, vegetation assuciatioigs, drainage develop-ment, totiographic setting.t id relation to landforjns, cultiiral utilizaition, etc. Cluies tothe subsurface are looked .r iii %..its ani gullies, and their attributes and angles of re-pose are noted. From empirical knowv ledge, the type idenitificatiun of a deposit allowsfurther interpretive ju~lgnacnts to be made which are nut diiectly discerniible. Such as-sociati&,ns pirovide the basbi for inductive and deductive reasoning within one oi severaldisciphlnes. As a simple cxainple,:kctive sand dunes are generally composed of sub.angular to rounded grains of reeistant mat#e.ials such as quartz and lia~c a characterisiKgrain-size distribution, pirosity, perin.;ab~iity, etc. The dunies arc generally poorly' con-iolid-tcd nid have characteristic shapes Lnd' slope angles.

Many other probable inferecmes canl be made about the dunec decos"it withvarying degCei~s of reliability. The making of mutually compafible~priniar) a-nd second-an; judgments from various lines of direct and indirect evidence it, all part of the inter-pretive procedure-the raethod of extracting information fromi remote sen~sor imagery -

Much of the buccesb and accuracy of the interprctafion nccrssarily (ependhs on thle sill,background, and initerest of 'lie interpreter (or interpreters).

isoulie The interpretive procedure for extracting information from avrial imager),is utlnedin many publications (F"rost, el al.. 1953, Lueder. 1959; Xnieri-an Society

of Photogramrnt-try, 1960). Thle tecimiques, were largely d-evlojied for ;Lw-,al phiotogra.phy bull can be adapted to other form~s vf remote ben~sor imagery. h i general, thle turrainl-oriented proce-dure. include a regional-to lot al appruatht is -dii' It thec patteri, ule-mentb

I,- f thle landscp lihe phy)sical, b~iologi wl, a nd cultu ral co inpoient-I., art 1na zed aidrelaed ogeherin 'rdr t obainmeaingul nfomaton.Thesc intcrpretti%. It.ch.

Iniqt-, whent used for anal) zing~ imagery other than. phlotgraplh% ixiust t mv.idrr the

unique energy forms and special operating characteristics of the sensing ~ystcmsinvolved.

The character ~i-h r- f common landforms a-. associated deposits are dis-cussed in a variety of geologic and geographic tests. For example, Thornbury (1954)prestnt-s a elassk~al ,.,erview of the field of geomorphology; and FMint (1971) gves a

Js comprehensive treatmenet oit glacial and periglacial landformns, deposits, and processes.

-~ (c) Remote Sensor Applications: Aerial photography continues to be the mostwidely used type of .emote sensor imagcry for deriving in~ormation on the phy.%cal,biological, and calturji components of the carth's st-rface. Panchrom-dic ~Ilms continueto be widely used, but other film types i-re increasingly ut izd such as U V. blacI; and

JLŽ white IR, crlnr, and color 1R. Various film/filter combinaltions have been shown Lo bevaluable for deriving information on terrain and materials, and, for some special andgeneral investigations, increasing use is made of film/filter combinations in special,raultiple-camera befupis. These provide simulitaneous covcrage across the entire visibleand near-visibie bf ectrum or disecrte segiatcntsc. Electro-opticalok'anning devices havebeen developed to provide similar coverage; the signall 4ata frum these sensors are moreamenable to electronic data prucesmsing techr.;qukts buW. the imager) usuo", lack. the uni-tary geometry of frame photogiahy in an effort to deicllop discriminatory signaturtdata, work, h,-, been done on investigating thz reflectance characteristies of surface me.-terials in differei-t en~ironments and under '.srious atmospheric conditions.

Improvements in coicir films (sliced, grain'ness. etc-) and processing tceh.niqucs 'rapid and controlled developing and reptodu-t ion) tsombined with narre wingcost margins ha.e helped to -%tnimula!c a ividler general use- of color film~s. Numerous ar-ticles have appeared in the literature or, th'o merits (if color and color IR films for dcri%-ing information o.-i earth matc~ial,, for general iie-stigationt, of phy)sit-al, biologicAl, .111dculture phenoritena, and for photogrammietric mapping (Reed and Rinker, 1968; Alison,

196; Aypricn SeietNofPhotogromrncry, 1968). nit _e films arc widel;, utilizedbccause of dibir gcrperallN high information tontent and c.i,;c of 1ntu'rprctation. Positivetranspa-rencits..-.pparc'ati,' allow maximurn d~scrinunatiun o~f detail. ('rifical f~ctoN. suchlas b.-n!i-ght, exposure. and volo, balance which should lit coil.ideredl for optimizing theresults of special color photo m~ssions.-ire outlined by hi tm:er anld Birdl (1970).

Althotglx not inl VOMMOtl 0.s,, Ultraviolrt- plwot-wraphy can he uniquelyutilizced fcr detectinganrd Wiommify ing, ertain tý pcw of material. such a., evaporite., and.'arb~watc which characieristi",all have high reflectan:7e% in the UV. lExperimenetal usehas also been umade of a hiih -resoiuition graIting snectrom;eter for iden; ifi. ing - ario.islumin~escent miterial.s mndvr natural swilight r"'isditit is. Xvtiwv UA -y tems (cathoderav tubes, rnercur% vapor lamps, and Li V lasers) %%hit nxmnulatt' ;n gnn'c vc iertain

ril ltrals. nitt rot'k'~such j. tale and dcoi iijt luov almi 'ween expv izete-Ii ed t

(Hemphill, 1968). Uniqbu. response chara-cteristics Evan hopefully be used &i a tni-ar.5for identification.

Thermal nfared scanner imag~ery may be useful for discriminating be-tweer . face materials and depiosits nut readily differentiable on other forms of imager.,. DS ifeecos in materials, either inherent or environmentally irzflu~enced, may giverise to distinct the= rnw p-gatures which can serve as a basis for dis-criminatioa andideartifi~cation. Ideally, thermal imagery allow s differentiation between ~edruck andur11curazolidated depoSits, between %arivus depcsits, and between different bdcktyp~es.D'ýpta-diing on a number of factor., signal contrast may be greatest either fox daylight ornighttime imagery for a particular range of bedrock and depozsit types.

The moisture content of zurface deposits greatly affects their thermal re-sponse. Th-ermal signatures causied b) anomalous moisture conditions cap. give ri.se toerroneous cnlsos uifoitrdfeences are inhcrently the resullt of natural

pru.perties-sands ve'rsus clay.~, for instance - theD a solid ba-sis Yor differentiation exists.Other eavironmental effects such as !ocal tempernuirc inversiorus can also give rise tanomakvuz signal and must be alivw',-d for. Thermall 1111 and als-O passiv'e microwaveimagery can be a %aluable supplement to more Conventional imager). A greater depthof :nformaition is zonietimes gzined by usaing a combipation of senbors. An example ofa multiensor approach to a probicmi is given by Orr and Quick (1971).

L Radar imagery, SLAR especially, can be used for evaluating surficial depos.its but, because of small sc~alc and limited resolution, onl) on a broad, general babis.Th -iaiae interpretive prfoce-dures, ubed for extracting information fi'oin photograph

0 ~can be applied to radar imagery with some neccssary modJifications. The radar image isa specialized presenitationt of the lanciscape- lacking the detailed infuimation content ofa photograph, however., unique Jec.action vcan occu~r ai, a result of radar cuergy/matterinteractions, and s1pcialized data can be getierated. With radar imagery, the broaderpatterns of iandform, rock, drainage, .ýegetation, and lanA us-c c-an be tiked effectively to

generate daaon th gnrltye irbuonand relative uatcrncs of surficiall 4epo~s-its. Some inferences can also bc madle op. composition and tte'.turc of surticial deposit,.Radar imagery is especially us.ftui in the initial stage., of regional investigativivs 'k. out

lrcgosfeatureý and distributions of !sarfate materiai i and, for !somte pvrtx~s,-,. i., lotal-

-y adecquate Iby itbelf. Radar imagcr' c.4n 4lro hý )L-tained at n~ighit and under a-me'sphecric conditions that would prohibit the actpai3ition, of photograyphy.

The radar scatterometer, wnich rnonit Wes the reflective response of earthim at crials -a funact io n of f euo n c N a nd look aagigl - c in ;dst bie usel it f jr dijL riminuarit innand identifying, theiw mattrials.

0

- L~~dI A=44wr gaa f2 tsof UIm u foU & B II §ctuc ad .V,

Pg&tziL1agc=5 of certam tvpes- of s-Rxia iatmzAls as was belkock. Tlie raloac-tive tkurgs mmiu and thodu=o~ and their dangbitr bT-jraocuds, and also pohimin-.10, we ,iddy present in = rsz id ,• ... T .n an - m m- hr ..- qmtnj... oftbhee dekmt- in SwAts- (em ipienkty of u..4eitia) •zws as the rauk of a mawber of facos wd~h ith d r~tw.off., Wr, aka wnathezix and rosme li:offy (Veooý

I hkisto) of the _sc~imeiits These z!!' d rnin miquely ;o &fr some s~ments aI partaculmr rairoadfire S gmatme which can be wed as a masof differaatiatio' Gamma-

ray tchiiques; can aL-o be used to map ributions of etain t*-pes of subwfface bed-rock unde wdual soi& and, in sowe cases, to traccsedinwtss back to source areas

.Air-droppabh. earth pemtrometrs are capahle of yiddrng useful &ata onproperties of surace, and near--rface materials and, also, data on thickneas, layeui V,and depth to bedrock for relatively shallow deposits- The data, however, is generatedfrom the point of impact only and mst be interpolated when applied to 2he immediate

surroundings. The penetrometer can senve as a ,sefful supplementary sensor to comnen-Stional im-ea•-.

302. COMPOSITION OF SURFICIAL DEPOSIT

j(a) Definition: A de2ermination of the gross mineralogical composition of4 surficial deposits.

(b) Interpretation Variables: The composition of a srfidal deposit can referto the actual mineral or rock-type makeup of the component particles (minerals suchas quartz, feldspar, and magnetite; rock types such as granite and basalt) or to the over-all size distribution of the component particles. Surficial deposits can be classified onthe basis of particle size distribution and terms such as gravel, sand, silt, and clay, to de-note certain particle size. designations. Such physical classifications'are useful and anumber of engineering properties are predictable based on particle-size classification

alone. Element 306 (Texture of Surficial Deposit) treats the subject of particle sizedistribution specifically.

The remainder of this discussion will treat mineral or rock-type composi-tion only. The determination of the composition of surficial deposits from remotesensor imagery is done largely through interpretive procedures in which numerous cluesare used to infer composition and offher properties. The identificat;on of a deposit asto type allows many subsequent judgments to be made.' This general sub jec is treatedin depth under element 301 (Type of Surficial Deposit).

(c) Remote Sensor ,tpplications: Many different types of sensor imagery canbe used to obtain info, -nation on mineral and rock-type composition of surface deposits.

88

7he Vnera wenits ad Swobtis o ram srv wvm ii rzgad weAmtw &meut 301 im Cig "aMjds ofi wrifauec" Fwt"M&M FbOICIORkY., plfi

larir co.k md coor EIP proibuy oifes the it 4e r, F oi r.-=modising in-fowafioa COU woA

STe SMSM gu asin -- o da and pinmat.-r sp~on amC401 Of Me&.weia F"Wtim(1112d~ic sEUcep(IJ:< radioactie raiw"K-,

of aMateuials oupin AtnIepos&t, and --;& idfonaimao mar be of aw in w!akinlgbruot. inferenms on comnpcition-

303. AREA OF SUWRIAL DEPOSRF

(a) Deficitia: A determination of die area of dtribfion of squfaxv deposiL

(b) Interprettio Variahes: There are necesry sjTs in the in:-prethi e pro-cedure that must be completed before the area of any fea~ure can be determined fr_:maer:al imagery. The feature must first be detected, recogized, or ieentifi d, and bourn-Ied. The identification of surface deposits has been discs urder element 301. De-termining the exact boundaries of a deposit can be as difficult as identifying it.

Once the deposit is outlined, its aerial distribution can be determined- Thiscan be done on a variety of remote sensor imageries of appropriate qu'ity, scale, arimetric fidelity. Area can be estima!ed or rn-sured with simple L-sk-type instrumentsor complex mensuration equipment. The pr(-cedures for these operations arm outlined ina r'mber of texts and manuals. Presuming that the boundai:s of a deposit lw:'e beenpreviously determined, the level of skili needed by an operator depends on the type ofimagery used, the measurement technique- employed, and the accuracy required.

Accurate horizontal measurem-nts needed for area determinations reqeiirethat the imagery has good two-dimension',i fidelity. Area determinations are possiblefrom many types of remote sensor imagery, although accuracy -will vary since the inher-ent geometry and resolution of imagery varies with the different sensor systems. Non-stereo imagery can generally be used for area determinatione' but sterco is alwlys desir-able as it iperease.s ease and accuracy of measurement.

The geometry of remote scasor imagery is, in •eneral, simple for most typesof aerial Fhotography ane more compiex for other imaging ,msor systems. Photographyprovides the Le,it overall resolution. The geometry and resolution capabilities of varioustypes of remote sensor imagery are dsiscussel in many articles, texts, and manuals someof which arc listed as references in paragra.ph I lb.

89

(c) mainage SarAMriabim Ac" jpbot, V 1'.1 apecia!y ustkdlpiotog* 1 prbalytbr awl Usieir wd iinagmy fm ara adermlatimoi a(safm

=111be Mde C~g d 2~tOMDi~tWfW iSK~aMfron Wp~riRCipal poix& of the

phouV2~i adilkou~vard to- 0ud the cegs, but thi cm be ca~y correctcd- Geon-

pAnorami photogaP,-sY is- epecially- a problem. h*ophoto of sufficeies quality andreolution cam aiso Ictide an excellenti means for defermiining - Pe-a of surface tieposits&

-Ame determinations can also be made from othier types of remote seunsor

imagery- Tek-.ision images can have good geometric fidelity and resolution-. Imatgeryi i ~from linz -seaing therumoi JR mid passive microwave sytems can be used for generalarea determin-ations, but spatial resolution iss much poover than photography (especiallywith microwave). lIn addition, there are many internal and external factors that cap. ad-

verse) 'v affect the quality of scanner imagery; image geometry is complex and rectifica-tion tteliniques are involved.

Areas of surface deposits can be determained rom radar imagery. Thegeo-metry of radar imagery, including SLAB., allows relatively accurate horizontal meca-surements to be made; however, the general small scale, limited resolution, anid tonalcontrast vmake the use of radar imagery practical1 only for large, well-defined depo~sits.

The laser profiler h as l1ittle direct application for determir.ing areas, of sur-* ~face deposits since it provides only line-trace data. As an accurate altimeter, however,

it can provide the means for calculating exact scale for supplemneutal photography. Ascanning laser, if developed, would be useful tor making accurate determinations of area

304. THICKNESS OF SURFICIAL DEPOSIT

(a) Definition: A determination of the depth of surfac~e deposits.

(b) Interpretation Variables: This discussion will be largely confined to thick-ness determinations of surface deposits, such as floodplain and glacial-till deposits,which arc formed by distinct processes and are associated with distinct landform.'. Thisis in keeping with the spirit of the discussion presented in element 301 (Type of Surfi-cial Depasit).

'rbp cai di material penetrating capability of the more conventional remotesensors such as infrared and microwave scanners and radar is generally limited to a few

90

firLtWattr and ds fr0== FhUI- icr- wre exc"F-W" d a'aM7r- bega niatmi hamo-peamm anid tramp-p~rent to ckerotagm~aet and ac x~bcad teMr at wt~ rpzin qeiesDcep pnxlrafim awd tbickmrmduialen can h*- made with s-emeall sixhct+-lýrdand akbrnec wasor_. Some of the _-man. and tcdiqe used for deterino vzterdej-h zre uFramd in dewnti lOi. T',he subet of thicamw & Iiaation of floating

icet is &-eed in clement 113. Gaciers and ice capsare m red in cement 310;spccu&M radar techniq'rs hae been used to sowmd ice cap sever-- thousand feet inthick.-ms

In general, the more convrntional airbxne remote sensors. both active andpassnv. sense earth surface and v-e -nar earth-stuface phenomena only. Deeper phe-nomena may '. detected but, largely, through secondan. effects detectable at the sur-face. Most of the data on subsurface properties and thicknesses of earth materials de-rived from conventional remote sensor imagery is inferred through interpmretie tecdniqn s ..

subsurface. Direct determinations of sbssurface properties and thicknesses can some-times be made where large expa, res exist or where smaller "windows" to the Subsurfaceoccur in the form of erosionzal gullies.

Interpretive procedures for determining subsurface properties and thick-"nesses of surface deposits rely heavily on identification of the type of deposit. Certaindeposits are characteristically associated with unique landforms and are the products ofselective processes of weathering, erosion, and trarsport (wind, water, ice, gravity, orcombinations of these). These deposits have ,haracteristics which are predictable to acertain extent. Once a deposit is identified as to type and origin, generalizatioms can bemade about its properties, distribution, and probable thickness. Numerous other cluescan also be used to indicate the thickness of a deposit or to make generalizations aboutdepth to bedrock, etc. This general subject is treated more extewmLvely in element 301(Type of Surficial Deposit).

There are several ground-based sensing techniques for deriving informationdirectly on subsurface properties and distribution and thickness of earth materials.Ground-based shallow seismic and electrical resistivity techniques utilizing artificial en-ergy sources are capable of good definition of surface and near-surface deposits. Theshallow seismic technique utilizes a shock device (explosive, hammcr blow, etc.) and anarray of geophones to determine material type, layering, and overall thickness of a de-posit by monitoring the rate of travel of the shock wave and the modifications causedby reflection and refraction. The shallow-resistivity technique utilizes active clecticalprobes and a monitoring device to determine material properties, layering, and overallthickness by measuring the electrical conductivity. There is an extensive literature onthe use of these shallow geophysical techniques. They can be used in conjunction with

91

- " ° .-'

2u""oW aSI ft&690Ma to FCO~i& Co9 Iemk v et a fw 1We~ Sag prk IS a AWArmft sdtdio (-.4c)ar, 14)

ReCae saNuig from,, aih. pbhtf(rml 2Ct'&Ui ,iruiMLe h:X of pro~und-basr-1 sesing, tecbniyas and foame =oiia~t-_ in the use 4~ otdhus. Arltvt ~sqiauic tecdznpae wo-ld he lzphr restricted to the druK,*, of tsq~adr dmvim and

aqVi q-miate inwsitofiulg sensom-. Actiwe abomeww reqa.4~iy roeappropratc!y h: mg antera, etc.- mounted to t a at. 5oi, &A -irbowsensing techiques are &lcssrd later in this prartat',x

(e) Remote Senaw Ap•licafiom Aerial photora y is commerfi used foiSinterpretihe imestiations of surface earth materials. Fhotcgraphy iv ca;able c4 -tceD]entdefirition, is rsatile, and is easi-y obtained. it can be used for mak•uV eitnmanes -'f thetLickness of deposits through interpltlime tedmiquets or for obtaining dii-a thicknessmeasurements where exposures permit. Vertical stereo photography would offer thesimplest geometry and panchromatic films, the widest iatitude of expqosu-r., greatesteconomy, etc. Color and color IR ffims, however, would generally be the most usefulfilms for making thickness determination.- since the identification of deposits and dis-crimination of boundaries would be easier to make. The actual choice of film for a spe-cific use, however, depends on a number of factors such as the nature, location, andgeneral environment of surface deposits, meteorological conditions, etc. Multiple photocoverage of an area may be desirable using a variety of film/filter combinations to per.mit maximum discrimination. Other remote sensors may have to be used in conjunctionwith phctography to obtain comprehensive data.

Aerial photography (vertical and oblique formats) has been used with goodresults !o obtain snow thickness data over courses where vertical, graduated markers havebeen set up (Finnegan, 1962). In the absence of established markers, estimates of snowthickness can be made using fence posts, etc., as heighl ,eferences.

Imagery from other types of remote sensors such as television, visible spec-trum scanners, thermal IR scanners, etc., also have use for making thickness determina-tions insofar as the imagery can be used for discriminating and identifying surface andnear-surface deposits and their properties. Some direct measurements of surface expe.sures are also possible. The factors limiting the usefulness of some of the non-photo-graphic sensor imagery include lack of routine stereo coverage, restricted resolution, andcomplex and variable geometry. The geometry of various types of remote sensor imageryin relation to area and elevation determinations is discussed in elements 303 and 313.

Some subsurface features and deposits (caves, water-bearing gravels, etc.)may be uniquedy detectable on thermal I R and passive microwave imagery to the extentthat they produce (directly or through bccondary effects) distinct thermal signatures at

92

the siwfaw-: The ddettimi of mith wl g rict~qito of ttwiir 5-3iipifcaim, bove-e?"r, gi~e no &end -tI iisafii of &P&h of ocrwmnxmt cc thidk=, of the -smife

katl-t o &pat!P.. Altcv'd •a•,th i wOiIemAly be Atl- -

Radar im2 .=- puticriy SLAR. has Lia- fow mAkng thidknes deienmina-tiow tut becm. e of ,egirtaIy .qmr _cqale and limitHe r•Atioc, cmhy on a broad baI-.Radar wiiqu- port..as the L 1n[scape ftoporapi•y. -zhucture- draý'ar, etc.) n -starkdetail, mod promider d,, which can leac to information on proper,,it of anficial mate-rmi-A in the form of s textress and *ones. The dicuniminat Rm of ,is-rials and tteirdistribution in relation 'o topopaphy allow some genetic identifica&in tf &dposits andassociated landforms from which interprethe judgments may be w3a- on peobable ihick-nes, depth to bedrock, etc.. as -reviouvy discsmsed. See article by Holmts (196 7).

"Specia~ized radar systems also offer promise of directly obtaining susb-ur-face data on earth materials. Lundien (1971) repmLs on the experimental umte of stept-frequency radar for detcrmining depths and layering in subsurface materials.

The air-droppable penetrometer is a specialized remote sensor (in less tk-.nthe strict sense) which is capable of directly penetrating earth materials to limiteddepths (depending on size, etc.) and telemetering data on properties and depth basedon rate of decelerdtion. The penetrometer has been shown to be a useful sensor formaking determinations on layering, depth to bedrock. and on the general nature of ma-terials penetrated (Marien, 1970). It has also proven highly accurate for determiningsea-ice thickness. It is limited in that it generates point data only. and the data must beinterpolated over a wide area from the point of impact. Supplementary remote sensorimagery could be used for this purpose. Development of a low-cost disposable pene-trometer would greatly increase its usefulness.

Such airborne geophysical sensors as magnetometers (which determinemagnetic susceptibility) and gravimeters (which determine variations in density) areused for relatively deep probing, on a broad scale, of earth materials. Magnetometershave special use for locating mineral deposits and determining rock type anid can pro-vide some general data on depth to bedrock. Gravimeters have general use for deter-mining rock type. shape of intrusive bodies, extent of sedimentary basins, et,..

specialized airborne systems for detecting subsurface features and

deposits are described by Barringcr and McNeil (1969, 1971). The first of these, theInduced Pulse T.ansient System (INPUT), has been used for some time in mineral ex-ploration. A large coil mounted below an aircraft is used to generate earth-penetratingpulses of clectromagnetic energ, which are monitored, and the electrical conductivity

of the underlying terrain is thus determined. The system is highly sensitive to local7COndLW•tivc Lodies and is capable of detecting ore bodies at depth (several hundred feet).

93 .4I.I

Thue spam appareni haf a wrmaI czpa1lil.y for Mfd~itn giz'tJ def iar. dand dav-gidh so-is and for puowiiab inforina~io cc Iaý.ineig,. adh~l to bedrotk, dquihto water table.. etc-.

The ErihaseT-l k- a rlatlisdv n-w sws•em which utiizes radio hequenryenz fromr IVLF and comAmercial broadcast stafions to obtan infermaiion on sdmor-face t-rran. Ground wares which penetrate dee_ into the earth's -sfu-c aw propa-gat- d fro, these stoabon for great dxisxncx T-- sours we moMItored by the

i4haseTM system. Signal behavor is lahr)- a function of the dectrical conductiv"i,of subsurface earth materials and can be translated into emeaningful geologic data.. Thesystem is appurtly capable of providing some infoauaLion on regional structural fea-tur-es and on local deposits such as gravels, permafrost, depth to bedrock, and depth towater table. Experimental use of the EPh-se-Th sytem has indicated that the broad-cast bands provide penetration depths varying between 10 to 100 feet versu 50 to 500feet for the VLF.

305. COLOR (RELATIVE) OF SURFICIAL DEPOSIT

(a) Definition: A determination of the relative color of surficial deposits.

(b) Interpretation Variables: Color, although a variable property, is importantfor identif)ing surface deposits since it contributes information to the convergent logicused in the identification procedure. Many factors affect the apparent color of surficialdeposits and the determination of color by remote means. Among these factors, mois-ture content and quality and quantity of illumination or sunlight are especially import-ant. Because these and other related factors are variable and because of inherent limita-tions in remote sensing systems, color determinations by remote means are relative onlyand are not exact. However, some forms of remote sensor imagery can approximate theapparent visual color of materials. The human visual apparatus, limited in sensitivity to;I small portion of the electromagnetic spectrum, also senses color but only approximate-ly. Certain types of color imagery are thus adequate for remote sensing investigationsand interpretations since the landscape is represented in colors closely related to thehuman visual experience.

(c) Remote Sensor Applications: Color photography is capzble of approximat-ing the apparent color of surface deposits. Color representation will necessarily varywith different film types and environmental conditions. Good relative color representa-tion is also possible with special electro-optical imaging systems such as television. Rib(1968) gives a comprehensive treatment of the vwrious descriptive, physical, psychologi-cal, and psychophysical systems used for designating color.

94

I ~306. W-VTURE OF UKF1UAL DEOS

(a) DefIieko A 4etenmintion of ibe Vrometric2I xzsec of the comrponamjarticlos of a smrfact depag hinde&.g size, shape, andaM !~mu

(bi) tepesimVauiable The abcae definition can be applied both to bed-rocks and to mateaials compiing unconsolited suface deposit (or "solk' in the

nering --sense). The empha4s is umAlhl on the sie didribution of the componentparticles. In general descriptions of surface deposks, or soils, broad terms such as •fineprained" or "coarse g-ained" can be used. Surface deposits can be more exactly dassi-fied according to size distribution of component materials; examples of size terms areg-axi, sand, silt, arA cla- as used in the Unified Soil Cla-.--ification System. Appropriatemodifie- can be used for each major siz• category such as silty sand if a sand containsan apprec'-ble amount of silt. Clays are also described in terms of the degree of plastic-ity exhibited. Classifications also usually include entries describing organic-matter con-tent if present in ignificant amounts.

(c) Remote Sensor Applications: Determinations of texture of surface depos-its can be made from a variety of remote sensor imagery. Most of ihe information isderived or infen'ed through interpretive techniques. These techniques and proceduresare described in detail under element 301 (Type of Surficial Deposit). Generally, pho-tography offers the best means for making determinations of texture.

307. MOISTURE CONTENT OF SURFICIAL DEPOSIT

(a) Definition: A determination of soil moisture content generally expressedin relative terms.

(b) Interpretation Variables: The moisture content of surficial deposits (or"soils" in the engineering sense) can vary greatly over a given area and also, with time.Thus, soil moisture determinations even when made by ground methods ai e valid only

for limited areas and for limited time periods. Especially affected is the surface or airýsoil interface which can dry quickly even after extensive wetting. Such dry surfaces canbe misleading since appreciable moisture may be present in the subsurface, especially inclays or clay-rich soils. Since most r'mote sensing systems sense surface phenomenaonly, determinations of subsurface moisture can be difficult.

The moisture content of surficial materials at any given time depends onmany interrelated factors among which are the type of material or soil, topographic set-ting, and availability of moisture. The moisture supply can be in the form of rain orother type of precipitation, surface runoff from surrounding areas, groundwater inflow,etc. Minor periodic wetting can occur from condensation phenomena such as dew. As

S95

an c~zM9C of dbe aitaIahmi of the abov faeots• diftienit surfamce uatc::suchas s-=d& and diay occurring im theimne top.grap~ic setting and -mt simi-lar con~-

ibons of moitre supply wl sabably have differcit moi4are ctest beca•es oftexturg uifficrncc, etc-. Conversely, simiar soil in dioanmiar topographic sicffings mayhave different moi4_ure cionterets because of rariatiowx in mdoiure suppk, drain,-g con-ditions- etc-. Factors and rafonships such as ibefe have to be ket in mind whtir evalu-ating moisture conditions of surface materials from remote sensor i.agz-.

Various types of remote snso imagery can be uscd to evaluate moistureconditions of surface deposits. An interpreter uses many direct and indirect dles tomake inferences on moisture conditions- Photographic tone~s, for insance, can be wsed

as more or less direct indicators of moisture leveis, within limits, since moisture tends todarken the natural colors of deposits. Vegetation a.-sociations, cultural modifications ofthe landscape, crop types (and vigor), etc., are more indirect indicators of general mois-ture condition: in surface deposits as are springs, seeps, and standing water bodies. Aregional-to-local approach as outlined under category 120 (Location of Groundwater) isadvocated for making general evaluations of moisture conditions in an area. With thLsapproach, all aspects of the landscape such as those outlined above, and including topog-raphy and drainage, are used in evaluating general moisture conditions and for maki..ginferences on moisture conditions of specific surface deposits.

Whatever the remote sensor system employed or the interpretive techniquesused, however, determinations made on moisture conditions, for the most part, will be.- lative in nature. Statements wili be made on the general wetness or dryness of surfacedeposits, or general estimates will be made on moisture content using such terms as low,medium, or high moisture content. More explicit statements can sometimes be madeunder special circumstances. The state of the art of remote sensing as related to mois-ture content of surficial deposits is such that only relative determinations are possible.

In recent years, however, work has been directed toward developing more

quantitative techniques for determining the moisture content of surficial deposits. Good

results have been obtained for test arcas where periodic sensing missions have been flownand ground and atmospheric conditions closely monitored (Schmer, et al., 1970). Thisempirical approach has resulted in the establishment of definitive relationships for spe-cific test sites which enable moisture conditions to be determined from remote sensordata obtained at select times and under select meteorological conditions. Work also con-

Stinues on ground-based tests and laboratory investigations on the effe~ct of moisture on

the reflectance characteristics and thermal properties, etc., of surficial earth in iterials.Such combined programs offer promise for the development of quantitative techniquesfor the remote determination of moisture content in surficial deposits under a variety ofenvironnmental conditions.

96

S• • • • •.a ----------- .

(c) 3Reno~ Aphafiam lFhotograpizy has.i&e zpication fow irnestigaig 3nosture: con~diton of surfidial deposis and f4r watfr resomrco investigation -

general- -Aaia phologm-ph allows an inteqxeter to siew the Iandicape 2E it wrcid ap-pear naually from the air (especially tree for color phirt•oaphy) and to study in detailthe vario components of the ladscape t•at give dues am to gtocral moistre conditions.These components include topography and landforpmr, sinficial depos-is, natr and arti-ficial 6,&zag channes and water bodies, vegetation amewlages, and landuse patternsPhotographic tones can also le used as genral indicators of moisture ronditions or formore spetific det--rminhtions such as may be obtaned by densitometric analysis of pho-tography acq.i.ed over calibrated test sites.

Infr-rd-ensit:ive films would probably offer the greatest benefits for de-termining moisture conditions in surficial deposits since there is high absorptance of in-frared radiation by moistmre. Color Ik films would also offer greater ease of .ecognitionof important supplemental indicators such as vegetation assemblages, drainage, and cul-

tural features.

Multiband systems, using various film/filter combinations or selective seg-men!s of the expanded visible-light spectrum, are useful for obtaining information onmoisture conditions of surficial deposits. Use of select narrow bands, especially overtest areas, shows promise for obtaining reliable data on moisture content. Applicationof multiband and other sensor techniques for moisture determinations is most promisingfor agricultural purposes where relatively homogeneous conditions exist at certain timesof the year-as for example, in low-lying, plowed fields in the spring.

Thermal IR and passive microwave sensors are also useful for making deter-minations of moisture conditions in surficial deposits. Moisture greatly affects the ther-mal response of surface deposits, and anomalously moist areas can appear as distincttones on infrared and microwave imagery. A certain amount of "depth" informationmay also be obtained, since subsurface moisture can affect the surface temperature (oremissivity) of deposits and be detected on this basis. Thermal IR and passive micyowavesensors are capable of excellent thermal resolution. These sensors show promise as a po-tential means of deriving quantitative data on moisture content of surficial depositseither used alone or in conjunction with other sensor systems. Imagery can be obtainedduring the day or night. Optimum sensing time will depend on several factors such asthe nature of the terrain, vegetation, season, and present and previous meteorologicalconditions. Missioni should be planned to obtain maximum contrast in ground signals.

Radar energy is sensitive to moisture in surface deposits (affects the strengthand polarization of return signals) and to any phenomenon which changes the conductiv-ity or nature of the dielectric properties of materials. Tbius, the physical basis exists forthe possible use of radar as a means of determining the moisture condition, in surficial I

97

q.mi

deposts, perhaps on a quantitathe basis. Tests by Dais, et aL (1966), &.3w premsfor ra6ar as a tool for remotely determining, by direct neans, the moisture and grouad-watea conditions of terrain.

j Gamma-ray emissions are attenuated by the presence of most"e in surfacedeposits. Emissions can be monitored and variations in signal count can be theoreticallycorrelated w•ih moisture content. Among other things, however, normal ground-radiation levels mtut first be determined. The technique would be most promisig forhomogeneous deposits ;%here normal ground-radiation levels would be fairly uniform.Deal, eta!. (1971), report the use of an aerial radiation detection and tracking systemfor deter'niting the water equivalency of snow cover by measuring the attenuation, bythe snow cover, of the natural radiation from the ground.

Various active and passive airborne geophysical systems, which monitor theelectrical conductivity of terrain, have general application for differentiating betweenvarious deposits such as clays, sands, and gravels and also for making gross determina-tions of moisture conditions of surface deposits. Two such systems, the INPUT andE-PhaseTM rsystem, .e described by Barringer and McNeil (1969, 1971).

308. MOISTURE PHAZE OF SURFICIAL DEPOSIT

(a) Definition: A determination of the frozen or unfrozen condition of theinterstitial water in i surficial deposit.

(b) Interpretation Variables: Freezing of the ground surface occurs each yearduring winter periods over exiensive areas of the earth-at high latitudes in temperateregions, and at high elevations at all latitudes. The frozen condition is usually only atemporary phenomenon generally ending with the onset of seasonally warmer weather.In high latitudes and at some high elevations, only partial annual thawing occurs; andsome ground remains frozen from year to year (permafrost). In these areas, also, relictfrozen ground, or permafrost, which is a product of past periods when climate wascolder than at present.,occurs. This relict permafrost in some areas such as the ArcticCoastal Plain of Alaska reaches thicknesses of hundreds of feet.

There are several aspects to frozen-ground investigations. In addition to de-lineating areas of general frozen or unfrozen surface conditions, there may be a need fordetermining the depth or vertical extent of the frozen profile and for determining icecontent. Problems may arise from the existence of a frozen profile beneath a partiallythawed surface or from the presence of a snow cover. The ground beneath a snow covermay or may not be frozen since snow can be an effective insulator. Generally, remotedeterminations of frozen or unfrozen conditions will be less complicated if the groundsurface is exposed.

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Frozen-ground investigations are aided by considerations of geographiclocation and climate, freezing indices based on temperature records, etc.

In high-latitude areas where continuous or discontinuous permafrost occursover extensive areas, its presence is commonly indicated by distinct surface features suchas patterned ground, peculiar drainage features, distinct vegetation associations, etc. Anexperienced interpreter knowledgeable about permafrost-its indicators, mode of forma-tion, areas of likely occurrence, etc.,- can use various types of remote sensor imagery tolocate frozen ground and to make many inferences about it.'

The pattern indicators of permafrost areas, engineering implications, andSinterpretation procedures for analyzing aerial photographs and deriving information

from them are discussed by Frost (1950, 1960). The identification of vegetation indi.cators of permafrost from aerial photographs is discussed by Stoeckeler" (1949).

The likelihood of occurrence of frozen conditions depends to a large extenton the type of surficial deposit, topographic setting, and availability of moisture. Depos-its such as gravels are more likely to remain unfrozen because of high permeability andlack of interstitial water. Fine-grained deposits such as silts are much more likely to befrozen. Because of the thermal effects of water, areas beneath streams, lakes, and pondswill most likely remain unfrozen; although, in high-latitude areas, relict permafrost mayoccur at depth.

(c) Remote Sensor Applications: Aerial photography has use for determiningthe general frozen or unfrozen condition of surficial deposits. Using photography, thegeneral nature of surficial deposits can be evaluated, in relation to the natural and cultu-ral features of the landscape, and key indicators of frozen conditions, such as distinctground patterns, can be identified. Vertical panchromatic photography has been usedextensively in the past for frozen-ground investigations. Infrared-sensitive films mayhave special value for differentiating between frozen and unfrozen deposits. Color andcolor IR films would be useful especially where special efforts are made to identify sur-face deposits and to judge their frost susceptibility in terms of grain size, topographicsetting, etc., or where vegetation assemblages are used as key indicators of the presenceof permafrost.

Thermal IR and passive microwave sensors would have special applicationfor frozen-ground investigations. Under select conditions, frozen and unfrozen depositscould be differentiated on the basis of thermal and emissivity differences and inferencesmade on the relative ice content in certain deposits. From thermal IR scanner imageryobtained near Barrow, Alaska, Hiorvath and Lowe (1968) noted that the frozen centralportions of low-center polygons exhibited tones similar to those from nearby frozenlakes indicating high moisture concentration in the central polygon areas. Using thermal

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and passive microwave sensors, it may also be possible, under certain conditions, to as-certain whether ground beneath a moderate snow cover is frozen or not.

The air-droppable penetrometer would appear to have use for determiningIlic frozen or unfrozen condition of surficial deposits and for making determinations ondepth of the frozen profile.

Various airborne geophysical techniques which measure the electrical con-ductivity of terrain would have general application for differentiating between frozenand unfrozen deposits and for general mapping of the distribution and thickness of fro-zen deposits. Two airborne systems which measurc the conductivity of terrain, theINPUT and E-PhaseiM systems, are described by Barringer and McNeil (1969, 1971).

Airborne seismic and acoustical techniques may also prove to have applica-

tion for frozen-ground investigations.

309. LOCATION OF FRACTURES

(a) Definition: A determination of the location and general extent of-linearlydefined zones of weakness in earth materials.

(b) Interpretation Variables: This discuE~sion will be confined to the airborneremote detection of naturally occurring fractures in earth materials such as joints andfaults. Some of this discussion would apply, however, to the remote detection of frac-tures in such man-made features as dams, roads, and airfields. Element 114 treats de-tection and location of fractures in floating ice, and element 310, fractures (crevasses)in glaciers.

Faults are fractures in the earth's crust along which significant displacementhas occurred. Faults may be extensive both horizontally and vertically. Joints are morelocalized fractures along which little or no displacement has occurred. Present-day faultmovements occur in seismically active zones of the earth. The San Andreas Fault ofCalifornia which extends some 600 miles is an example of an extensive active faultsystem.

Various types of remote sensing imagery are used to detect fractures pri-marily through recognition of characteristic surface linear trace and anomalous orienta.tion of surface features, deposits, streams, lakes, etc. Fracture zones also can have highmoisture concentrations (from runoff, seepage-even geothermal sources) which may,i14 in their detection-the fractures exhibiting distinct tones on photography and thcr-real imagery. Because of the moisture environment, fracture zones may be enhanced by

I 00

j~fi or &--ir._yc dizradexisfic veptatiomi which may be used alsc- as a basis for

Fr= t • t zones can also be sites of mineralization and miy have high mag-netic and radiation levels which may be detectable.

(c) Remote Sensor Applicatioms: Photography bas been widely ustd to detectsurfame fractures. Large-magnitude iractures, some previously unknown, have been de-te-ted from photography (therma. imagery also) obtained from the Apollo program.Low-sun-angle photography has been used to enhance subdued wopography and strue-

tural features in geographic areas containing highly reflective surface materials andsprn-e vegetation ,11owar. and Mercado, 1970). Panchromatic and black and white IRhave been the most widdy used films for detecting surface fractures. Color and colorIR films (prinis or positive transparencie.) would also be generally useful. Choice of

. camera. film/filter combination, and photographic format (vertical, oblique, etc.) woulddepend largely on the geographic area to be investigated, ground conditions, including

.. � - -pe and profusion of vegetation, and meteorological conditions. Choice of scale woulddepend on the size of features being invetfigated and area to be covered.

Hackman (1965) used aerial photography to investigate faulting and gen-eral disruptions after a severe earthquake in Alaska. Earth crustal movements have beenmonitored and measured vs;ng aerial photograph, obtained over ground reference sta-tions (Woodcock and Lampton, 1964). NumerousR fracture analyses have also been con-ducted using aerial photography (Trainer and Ellison, 1967).

Thermal IR imagery has been used for location of surface and near-surfacefractures. Because of moisture concentrations and differences in texture, etc.. of mate-rias, surface fractures tend to show up well on thermal IR imagery. Near-surface frac-tures are also detectable to the extent that they influence surface materials and condi-lions. Best general results are obtained with pre-dawn imagery. Thermal IR imagerycan be a valnablh tool in itself or as a useful supplement to photography for conductinggeneral investigations. Mosaics can be made from thermal ima_,3ry if careful proceduresare followed during a;rborne acquisition, and these can greatly increase the general use-fulness of the imagery (Williams and Ory, 1967).

Radar imagery, SLAR in particular, has special use for d-te, g surfacefractures and evaluating the overall structure of diverse terrain. Radar imagery tends toemphtsize morphologic aspects of tcrrain including drainage channels. The generalsmall-scale and wide-area coverage of radar imager) makes it more su-ted for reconnais-san-, and detection of large-magnitude structures than for detailed investigation ofsn~aler features. Much depends on the relatie orientation of the radar with respect tothe ttrraic. N-em morphologi -esults are obtamed uhi'i the radar is flown at low angles

10 1

* •parallel to the geologic, structural, and topographic grain (Wise, 1967). Positive trans-parencies probably yield the best results (Reeves, 1969). Radar imagery is also a valua-ble supplement to photography.

v.gt Radar has a general day/night and all-weather caiability and can penetratevegetation to a limited extent depending on frequency used. False structural linears,however, can be generated by rows of trees in addition to stone walls and other lnear jfeatures both natural and cultural.

0,N on-imaging sensors such as gf.mma-ray spectrometers and magnetometers

have some general use for detecting and loating fractures and fracture zones.

310. LOCATION OF GLACIERS

(a) Definition: A determination of the location and general dimensions ofglaciers and associated features.

(b) Interpretation Variables: This section on glaciers was written in conjune-o, 'tion with the ice elements outlined under "Hydrologic Elements" ('100 Series). These

other elements should be revieved along with this presentation.

Glaciers are large active natural accumulations of ice and snow generallyoccurring as tongues flowing out from larger accumulation zones-ice sheets, ice shelves,and ice caps. They occur in the polar, regions and in variovs mountain ranges in all lati.tudes being the prodet of positive snow regimes. , -tted~by various climatic and t6po-

V graphic factors.

The features of glaciers gnd glaciated topography are unique. In mountains,glaciers give rise to such features as serrate ridges, cirques, U-shapid valleys, kame ter.

-; ~-races, and inoraines. Deposits include glacial tills aud outwash gravels. Mountain gla-ciers generally exhibit linear bands of incorporated materials, and the strean fed byglaciers are characteristically braided. The glaciers fed by continental ice caps may notexhibit all the features typical of mountain glaciers, but processes of movement andmany of the features are similar. Glaciers arc d.scussed and illustrated by Thornbury(1954), Flint (1957), and Lueder (1959).

Glaciers, because they are generally predictable in occurrence and large inmagnitude, are easily recognized and located. Remote sensor imagery has been used inthe past for locating, mapping, and monitoring changes in glaciers (seqtuential imaging)

.7.= s . and for detailed studies of glacier processes and environments (Konecny, 1964; Case,1958).

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The glacier environment is complex having elements of ice, snow, water,rock, soil, and vegetation. The glacier itself i5 also very dynamic physically, thermally,and in all other aspects.

(c) Remote Sensor Application: Photographic systems of various kinds havebeen used for location of glaciers and general glacier studies. Panchromatic and pan-

- • chromatic IR films have been the most commonly used. Color and color IR films arebe'ng used more frequently for both general and special studies. These films allowgreater discrimination between the various features and materials in the glacier environ-ment, including greater distinction between snow and ice zones, and greater definitionof lineations, open crevasses, !neltwater channels, and ponded water.

The complex glaiewr environment is also an ideal location for experimentswith multiband and narrow-band sensing tz., haiques. Multispectral sensing tests bavebeen carried out on South Cascade Glacier, Waahingtorn. by Meier, et al. (1966).

Low-sun-angle photography can also be of use on glaciers, ice fiel&d, andice caps for outlining subtle surface features inch.ding snow-covered crevasses.light-levtl photography may also provide good images of glaciers at night under idealconditions. Both of these photographic techniques may be particularly uscful ia polarregions where long periods of low-sun-angle and darkness are common.

Because of the generally large magnitude and ease of recognition of glaciers,non stereo, small-scale imagery would probably be adequate for general location and re-connaissance purposes, but, for detailed work, large-scale tMereo imagery would be re-quired. The distribution and size of glaciers also allow the use of high-altitude, small-scale imagery obtained ft~r reconnaisbance purposes. Simple recognition of outstandingglacier features can be made on photogiaphic imagery by a novice interpreter, however,any detailed anlysis would require the services of a trained interpreter.

Glaciers can be readily identified and located on thermal infrared imagry.The imagery also has sufficient resolution and contrast for more detailed inveb'igaticns.A wealth of thermal signal contrasts is provided in the varied glacier environment. IRimagery may be used alone or in conjunction with conventional photography for addi-tional information content; thermal imagery can be obtained at night under miuderateatmospheric moisture conditions.

"Poulin and Harwood (1966) discuss the detection of thermal anomalies ongladcers and their significance. IR imagery permits discrimination between snow-coveredice, rock, and soil boundaries and allows evaluationb to be made on the various stages offreezing of glacier lakes and the relative depth of bnow on the lakeo. Dicrnmination canalso be made between active and inactive stream dcannels. The dIf.erential thermal

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..- S,"' -"- . - - ° -IfV

signals can be used as clues to dynamic processes occurring on and within the thermally"K sensitive glacier ice mass.

S" "IR radiometers and spectrometers can also be used to give additional infor-nmation on the thermal regime of glaciers and car be used in conjunction with IR scan-

ners. Use of IR imadgery and data for detailed analysis of glaciers and glacier environ-ments requires a skilled interpreter; for simple location purposes a less skilled workerwould suffice.

Thermal IR imagery has been used on the Greenland Ice Cap to locatesnow-coveed crevasses which were undetectable or only slightly evident from th- air(Rinker, 1966). Although low-sun-angle photography will sometimes help to outlinethese features, they are much more apparent on IR imagery. The crevasses, being openfeatures, hold air which maintains a relatively constant temperature. This air pumps inand out of the crevasses and gives rise to a thermal signal on the IRI imagery which gen-erally contrasts with the signals from the surrounding surfaces. In general, the crevasses

- will appear colder during the day (u hen surrounding surfaces are warmed by the sun)and warmer at night.

Detection of crevasses is extren'cly important for planning cross-countrymovements of men and equipment. In addition, vchicles and the snow -packed trails of

C 1-4vehicles can generally also be detected on IR imagery.

Microwave imagery can also be used for glacier location and study in muchfhe same mariner as IR imagery although spatial resolution is much poorer. Microu aye,

C howe,,,. hab the advantage of being able to obtairn imagery under conditions of atmos-pheric moistur- which would inhibit use of thermal IR.

1ltigh-frequent y ,LAR can rapidly provide quality imagery of glacier areas.The small reconnaissance scale ot 1-1- imager) has sufficient resolution for general btu-dies of glaciers. Gross surface features c,, be generally identified; these include linea-tions and crevasses in the glacier ice, major dia,.-es in roughness and flow patterns,major ice/rock boundarie., lineations in bedrock, anti :iajor drainage patterns (depend-ing on amount of relief). The strength of the signal returns Jn.,ends or, the ty pe of ma-terial, surface roughness or relief, and orientation with respect to .,dar sensor. Leighty(1966) lists the Narious: sVrfacc materials of a glacier area (margin of tht ':reenland IceCap) in order of gencrall) dinminishing signal return: snow, glacial ice, soils ai.J rocks,lake ice and sea ice, and open water. The snow-packed trails ana roads on the ice (,palso showed up well on the imagery presented by Leighty (1966).

,, Radar returns from glacial ice may be influenced by ice temperature andsarface moisture (reflectihe returns being stronger from we! ice) as indicated in "tudics

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\ ' 4 , --- ,¢ C

int.. .. . f 4

by Sheps (1957) of PPI radar imagery (Xband) of Greenland versus Antarctic glacialconditions.

Radar can provide imagery in daylight or darkness and under adverseweat.er conditions. It has proven to be a valuable reconnaissance sensor in the Arctic.Use of radar imagery for glacier studies requires an interpreter experienced in radarimagery as well as in general glacier investigations.

Low-frequency depth sounding of glaciers and ice caps is discussed underthe category Ice Thickness (113).

The laser profilometer has uses for study of the surface features and rough-nhess of glaciers but not as a prime locating sensor. The penetrometer, also, althoughpotentially useful for specific sampling programs, is not a prime locating sensor.

"The environmental factors affecting the acquisition and interpretation ofremote sersor imagery for study of glaciers are largely the same as tho-e discussed underIce Type (115). In addition, however, the high elevation of many mountainous areaswhere glaciers occuf may create operational problems in acquiring imagery, and thegreat variations in relief may affect the mensuration quality of the imagery -especiallyphotography. Certain environmental phenomena, such as tht occurrence and intensityof diurnal winds and temjcrature iAversions, may also be more prevalent in glacier areasthaii in !cs'• diverse terrain.

311. LOCATION OF VOLCANOES

(a) Definition: A determination of the location and general dimensions of vol-canoes and associated features and deposits.

"(b) Interpretation Variables: A volcano is "a vent in the earth's crust fromwhich molten lava, pyroclastic materials, volcanic gases, etc., issue" (American GeologicInstitute, 1960). Topographically, the term "iolc'.wko" refcrs aLo to the cone or moun-tain which is sometimes built tip from extruded or ejccted materials.

There are many ty pes of volcanoes and many cOassification, based on type.iuf eruptions, magnitude, and nature of build-up of %olcaric mass, etc. Volcano classifi-.ations are reviewcd by Thornbury (1954). Volcanoe! may exhibit cones or cone-likemasses of basalt and/or cinders, be of large or small proportions, ;.id exhibit craters orcollapsed structures. Eruptions may take place along extcnsic fissures and form lavaplateaus withott mu formation ot cones or .qmilar features. Volcanoes may occur ind:"%idually or in groups, be N outhful, and exhibit a bold outline or may be old and exten-siv-,ly eroded. Little or no surface trace may be present. or only a ,.olumn or ridge of

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r , aAT

"rock may protrude above the ground surface marking the site of a neck or pipe of a"former volcano. Identification is mosL simple in the case of a well-developed, activevolcano.

Active volcanoes occur in distinct geegraphic areas of the earth's surface,characteristically in a, tive zones or belts such as the circum-pacific belt. Inactive vol-canoes also occur in these zones and also in old mountain chains throughout the world.The location of many of these ancient volcanic centers is known only approximatelythrough such indirect evidence as thickness trends of associated extensive volcanic

") •deposits.

/ In regard to remote sensing, volcanoes, like other natural terrain features,should first be broken down into prime characteristics and then evaluated in terms ofthe remote sensor or sensor combinations bcbt •uited for acquiring information on thesecharacteristics under given environmental conditiono. The prime characteristics of vol-canoes, some of which have alreadý been mentioned, include the volcanic mass or cone,crater, fisures, active gases, lava, and pyroclastic deposits. If the volcano is active, itssurface and subsurfrce heat sources can also be used as a means of detection. All of theaLlove characteristics help to identify a structure as a volcano and serve as a means ofinterpreting its processes, relative age, geologic history, etc.

A crater is a prime characteristic of a volcano. When the crater is of excep-Stional magnitude, the term "caldera" is generally used. These craters may be explosive

in origin or due to a combination of explosion and collapse.

Other crater-.ke features which may not be volcanic in origin exist on theearth's surface. Some craters, such as Meteor Crater, Arizona. are thought to be meteor-

• •s: impact sites. The terms "cryptovolc~anic" and "astrobleme" have been used to refer tocrater-like structures of doubtful crigin. Bomb craters, excavation pits, etc., may alsosuperficiefly resemble volcanic ,.raters. Much research on crater morphology and mech-"anisms has been stimulated by the lunar exploration programs of the U. S. and U.S.S.R.

(c) Remote SenAor Applications: Photography, especially ver;ical panchromat-ic, has bcen the most ommonly used type of remote sensor imagery for general goo-morphological investigations of volcanoes. Volcanoes have been identified and located,and their deposits and geologic histor) of growvth and erosion have been investigatedwith the aid of photography. The generi! application of photograph) and other typesof remote sensor imagery to the study oi volcanoes is reviewed by I ezer (1971).

Useful scales for photographic (other imagery also) detection and study ofNJlca,.oes will depend on their size and boldness of expression and resolution and over-all qub !ity of the photography. Uweful information may even be obtained from orbial

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,2,

imagery. Active or youthful volcanoes will generally be easier to identify than old andsubdued onea. Novice interpreters should be able to detect and identify well-definedvolcanoes even from monobcopic aerial photography, although stereo viewing is ala)ydesirable.

S4 Color photography and color IR would probably be more useful than pan-chromatic for detailed investigations of volcanoes and volcanic terrain. Discriminationof materials, vegetation, and drainage features would theoretically be easier to makeusing color and color IR films. Multiband photography would also be useful for investi-gation of volcanic materials and %olcanic terrain as would quality imagery from electrooptical imaging systems. Good interpretive results, for instance, have been obtainedusing television-type amagery of the moon's cratered surface.

SThermal IR scanners and radiometers have been widely used to detect andntudy active volcanoes. Detection of new volcanoes has also been accomplished by

high-rebolution thermadradiometc• operating from orbiting platforms. Thermal ;magtr)% can provide information on surface and subsurface thermal patterns of volcanoes.

¢ Near-surface vagma concentrations and active conduits can be detected

"and the migration of molten lava traced with the use of thermal sensors. IR spectropho-oQ tomeers have been used to provide information on the concentrations of various vol-

canic gases (Naughton, et al., 1969). Thermal imagery is also useful for differentiatingbetween various lava flows and other volcanic deposits such as ash layers.

Radar imagery can be used for detection of volcanoes especially on a recon-nai.,sance basis. Large, well-defined volcanoes should bt easy to identify by shape alone,"but more subtle features may escape detection. Volcanic materials should also generatecharacteristic identifiable patterns on radar imagery. Radii scatterometers have been

A •used experimentally over volcanic terrain to produce data on surface roughness, particlesize, and topography (Quade, et al., 1970).

Gamma-ray sensors, magnetometero, and gravimeters have highly specialized"uses for the evaluation of volcanic areas.

0

S,,312. LOCATION OF LANDSLIDE PHENOMENA

(a) Definition: A determination of the location and general dimensions oflandslides and related phenomena.

(b) Interpretation Variables: A landslide can be defii.ed as a "udden movement

of earth and rocks down a steep slope. (American Geological Institute, Glossary of

10713

-, -• .q -r• - -j

"Geology and Related Sciences, 1966). The term "landslide" can also refer to the trackor sear left by the slide and the materials involved.

Many varieties of slope movements can occur. They aAe classified accord-ing to the type of material involved, kind of movement (rotational, translational), rate

0 0 and magnitude of movement, etc. All are debris movements or mass wasting of various

kinds and have a variety of names, for instance, landslip, avalanche, rock-Jide, mudslide,earthflow, and slump. Some slope movements are gradual and of limited distance;others are catastrophic and can move deb.ris great diatances. Classifications and detaileddiscussions of landslides and related phenomena are given by Sharpe (1960) and Eckel(1958). Eckel uses the term "debris avalanche" in much the same sense at the abovedcfinition of landslide. A sudden mass movement consisting largely of snow and icewould presumably be referred to as a snow avalanche.

Many factors affect the strength of slope materials. Some of these are:

"the type of material-its composition, structure, density, porosity, permeability, cohe-sion, and internal friction of p,,articles; steepness and length of slope; soil moisture;and type of vegetation. Mo:sture content is an especially important factor, because itlessens the strength of the ,oil or rock mass b, ;ncreasing pore pressure and weight.Slope failures characteristcally occur after periods of heavy rainfall. Earth tremors areexceptional phenomena tiat may cause otherwise stable slopes to fail at any time. Mancan create conditions leading to landsliding by logging and building roads and dams.

In addition to identify',g and locating landslides and like features, there

are also the problems of identifying landslide-prone areas and predicting landslides. InIthise report, the discussion of remote sensing of landslides will be largely limited toproblems of identification and location. The other two categories are more artful inapproach and require an extensive knowledge of hlndblid phenomena-especially theprediction aspect.

0

The most apparent feature (,f a landslide that would aid in its identificationand location would be the &zar marking die origin and path of the slide. All downslopedebri, movements, however, do not exhibiit obvious scars or distinct sliding planes; and,in these instances, other identifying features must be used.

The slidr- =r can he recognized by its downslope, elongated shape, andcontrast with surrounding terrain. A tresb, slide of large proportions, possibly involvitngthe removal of trees and other vego.tation, would theoretically be easy to recognize. Oldscars would be less evident espcciailh, if reforested, although the scar pattern could be re-flected in the reforestation pattern (the outline of the forest pattern, its composition,and age distribution). Such vegetation patterns may alhso serve as. indicator,, of the ap-pro, imate age of the original disruptive event.

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0- ,

A landslide scar usually persists for a long time and may be marked by astream or gully. Often, a landslide or associated event bets the stage for subsequent dis-ruptions. Movements of soil rock, and other debris can occur along the original slidepath. Cracks may appear above incipient slides. Such considerations enter into land-slide prediction and identification of landslide-prone areas.

A landslide may also be identified from the downslope accumulations ofrubble. This is especially true in situations where debris is strung out on the glacier,

0.• # playa, or other contrasting surface. In addition to the recognition of the adtual debrispile, cone, or trail, the disruption of drainage and other patterns would serve as indi-cators of landslide activity.

Talus cones may mistakenly be identified as landslide rubble by an inex-. .". ... perienced interpreter. The processes of accumulation are somewhat similar although

the time frame is drastically different. The gradually accumulated talus pilw or coneswould, however, serve as indicators of potential landslide areas.

(c) Remote Sensor Applications: Aerial photography is probably the mostuseful remote sensor system for identification and location of landslides and relatedphenomena. It is the most common sensor system used in the past and probebly will"be in the future.

Swanston (1969), for instance, reports on the results of an extensive air-photo survey of landslides in the Tongass National Forest of southeast Alaska. Morethan 3,800 large debris avalanches and flows were detected, most having occurred inthe last 150 )ears; older movements were generally not apparent on the air-photos(pa..chromatic).

6

Stereophoto coverage is generally desirable for landslide detection but notalways esbcntial. Large, fresh slides may be detected by a less experienced interpreter;but older, more subtl,,e, or obscured features would require a more experiencedinterpreter.

Vertical photography is generally adequate, but occasionally other photo-graphic formats such as oblique may be more desirable. Depending on type of ttrrain,vegetation, atmospheric conditinb, etc., one special film/filter combination and scalcmay yield more information than another.

In a -omprehtivisive studt in the southern Appalachian Mountains by Poole(1969), a %ariety of ,lope-failurc forms from sheet-wash erosion to large, ,u;, tit land-slidcs %cre investigated, and evaluations icre made on the capability (if variou,, types ofaerial photographiN to Nuppl% information on them. Criteria for idenitf% ing the,-, feature,

"109

were also given. Color and color IR transparencies proved excellent for study of allslope-failure forms including major and minor characteristics, associated vegetation, andsoil moisture conditions. Small-scale photography on the order of 1:20,000 was judgedmost appropriate for general stud _ (large and small features), and scales on the orderof 1:10,000 or larger were considered more appropriate for smaller features.

Dishaw (1967) reports on the use of very small-scale photography (on theoraer of an inch-to-the-mile) for detecting massive landslides whose great dimensions"make them difficult to detect on the ground or from large-scaic imagery. Dishaw alsooutlines techniques fo: recognizing these massive alides from air photos.

Measurements of landslides are possible on imagery of appropriate scale1 and quality. Snow avalanches have even been sequentially photographed from ground

stations while in progress, and critical measurements have been made from the photog-raphy (van Wijk, 1967).

Thermal infrared imaging sensors would have application for location oflandslides. The low-light and night capabilities of this sensor may be especially usefulin certain instances. Thermal contrast between the alide area and its surroundings, how-ever, would have to be sufficient for detection and identification. A landslide wouldexpose new surfaces with associated water condlitions and would disrupt normal thermalpatterns ,uch as vegetation. Such thermal contrasts, therefore, may be common. Ther-mal infrared imagery might also be valuable for studying the moisture regime of a slidearea-a critical factor. The limited resolution of the imagery would be a restricting fact-or, and its use would require an experienced interpreter.

Non-imaging radiometers and lasers would have little application for land-slide location. The point data or line trace presented by these sensors may be useful forproviding quantitative data on the dimensions and thermal regime of a slide area butnot as a primary detector.

Other non-imaging systems, such as magnetometers, gravimeters, penetrom-

eters, etc., would generally have little application for detection of landslides. The pene-trometer, however, may have value in investigating subsurface conditions in slide areas.

Radar, especially SLAR, may have some usefulness for locating landslides.In general, however, the limited resolution and small scale of the radar imagery wouldmake detection of landslides difficult except for very large features or special situationssuch as large slides on vegetated slopes. Radar imagery may be more useful for search-ing for prime landslide areas on a reconnaissance baWi6. The presentation of topographyand structure in stark outline over large areas would be useful for suih purposes.

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Supplemental photography at large ocales could be subst-quently used for closer inbpec-tion of suspected landslide areas.

Environmental factors affecting the identification and location of land-slides from aerial imagery include obscuration by vegetation, snow, and ice. Otherfactors include the magnitude of the slide feature, its boldness of expression, and itscontrast with surroundings. Atmospheric factors are always a consideration.

313. LANDFORM ELEVATION

(a) Definition: A determination of the vertical distance of an object or featureabove some datum.

(b) Interpretation Variable3: The terms "elevation," "height," and "altitude""are similar in that each refers to 1he vertical distance above some stable plane of referenue, although, there is a tendency in the United States to limit the term "elevation"to the vertical distance abo~e mean 6ea level. Other elements in this report treat special

S..height or elevation topics such as tree height and bank height. Element 314 (SlopeAngle) also contains pertinent irform ,tion.

There are several rcmote sensors which can yield data on elevation or verti-"cal distance. of features above given levels. Some ol these sensors produce images andothers, direct point or line data. The inagery from these various -ensors differs in qual-ity and resolution. Vertical aerial phu...graphy is probably the most commonly usedimagery for producing elevation data, i1, is versatik and ib inherently capable of excellentspatial resolution.

(e) Remote Sensor Applications: All photographic systems producing dimcn-sionally correct or correctable stereo imagery of appropriatt, quality, scale and resolutioncan theoretically y iuid useful clevation data. This applits also to the various photograph-ic imager-. formats such as vertical, oblique, and strip. Elceation data are also possibleon a lirait,'d basis from select single photographs; but, in general, stereo coverage is ne-cessary. Vertical aerial photography, generally, has the simplest geometry; other for-mats such as panoramic are more complex.

* . ,-, A vadiety of methods may be used to extract elevation data from photo.graphs. Elcationb of features can be simply estimated or measurements made with

: " desk-type instrumentb or sophisticated plotting machines. The accuracy and precisionof sbcli methods are affected by a number of factors chitf among wvhich are scale, oNer-all control, and image quality. The usefulne.s of any scale depends on the size of thefeature to bt niasured and the degree of accurac) required (in ddditioi to contrast andimage quality).

S11l10

Ci

The determination of elevation and slope data from imagery generated byelectro-optical systems, thlrmal scanning systems, and passive microwave systems is dis-cussed under element 314 (Slope Angle). Techniques for obtaining elevation and slope

. •data from radar imagery are also discussed under element 314.

A combination radar altimeter and aneroid barometer-the Airborne Pro-file Recorder (APR)-is used to zbtain elevation and slope data on terrain. The radaraltimeter measures the vertical distance between the aircraft and the terrain, and a dif-ferential barometric instrument records the deviation of the aircraft from a set baro-metric datum. A profile of the terrain surfac: is thus obtained. The radar APR's in-cdude low-al titude FM and pulsed radars and specialized narrow-beam equipment.Height actoracy of the APR is affected by the fact that the signal returns are integratedover the retire area of illuminatio:,; and, in locally irregular terrain, profiles may besmoothed. For a 1-degree, narrow-beam APR, the ground diameter of the area of ilium-ination from a 5,000-foot altitude would be about 88 feet. Height accuracy can be onthe ordei of .5 percent of the flight altitude. £he narrow-beam APR can be used at lowor high altitudes and under adverse weather conditions during the day or night.

The laser terrain profiler (LTP) operates in a manner similar to the AM',except that a very narrow beam of light is usc.0 for ranging. Depending on the type ofequipment and narrowness of ihe taser beam, the illuminated spot cn the ground canbe only a few inches in diameter from an altitude of 5,060 feet. Under good conditions,the height resolution can be on the order of .2 percent of the altitude. The LTP is es-pecially useful for obtaining height data on small features, although background "no: L"can be a problem. Profiling may be conducted with a continuous laser or pulsed I:. er,the continuous laser generally having a greater accuracy. The continuous laser pi ,filercan be used from high altitudes and the pulsed laser, theoretically, from very hlig Altitudes. In addition to providing a profile of the terrain surface, the LTP (APh ,,io), ,mbe used as an accurate altimeter to provide altitude data for calculating exact bcale forphotography.

The LTP generates a linear surface profile of the terrain and is generallysupplemented with some type of track photograph) for loc;ation purposes. It is thcoret-ically possible to develop a scanning laser (bome obvious ,hortcomings, howevcr) in"which a much wider swath would be illuminated. Like all sensors, the laser is afectedby certaln environmental factors such ,, sunlight, atmospheric temperature, and moibture. The total interaction of the essentially monochromatic light beam of tle LTPwith various surface materials is also incompletely known, and anomalous returns canaffect the profile data. Despite some limitations, the L7P is a useful profiling sensor.

112

314. LANDFORM SLOPE ANGLE

(a) Definition: A determination of the angle at which a surface deviates fromthe horizontal.

(b) Interpretation Variables: The slope of terrain features can be, expressed interms of degrees or percent or as a ratio. Slope can be determined by any methodwhich yields data on horizontal or map distance versus elevation. Slope data can be de-rived from a variety of remote sensor imagery producing a dimensionally accurate imageof suitable scale. Sensors can also be matched to guarantee accurate height and hori-zontal distance data. Since elevation data are necessary for calculating'slope, element313 (Elevation) should be read in conjunction with this discussion. Accurate horizontaldata are also necessary for making slope calculations and for determining exact locations.The geometry of various types of remote sensor imagery is discussed under element 303(Area of Surficial Deposit).

(c) Remote Sensor Applications: Aerird photography is most commonly usedfor obtaining slope dati. Photography inherently has the best overall resolution andmetric quality of the various types of remote sensor imagery. Verticalphotography isthe easiest to work with and has the simplest geometry. Measurements and rectificationprocedures are more complicated with other photographic'formats such as oblique andpanoramic. For certain ptuposes, however, formats other than vertical will be desirable.Some slope information (height/horizontal distance) is possible from single vertical pho-tographs, but stereo coverage is generally necessary. Othophotos can be helpful in de.termining slopes and exact locations.

The selection of photographic format, film, and scale for determining spe-cific slope data will depend on the, type and magnitude of. the feature or features beinginvestigated and the prevailing environmental factors including atmospheric conditions.Color and color IR films wculd offer the greatest ease of discrimination of features anddelineation of boundaries; however, for the most simple slope determirntions, otherfilms such as panchromatic would suffice.

The level of skill required to extract slope data from photography (othertypes of imagery also) depends on a number of factors including the type of instrument-ation which can range from simple to complex. Generally, a certain level of skill is re-quired for even simple slope determinations since a representative slope must be chosen,various ground conditions (vegetation, snow cover, etc.) must be dealt with, and accur-ate measurements must be made in the true, down-slope direction (analogous to true dipand apparent dip in geologic parlance). Estimates of slope also require a certain levelof experience. Novice interpreters tend to generally overestimate the slope of natural

113

terrain features due to vertical exaggeration when using photography. Slopes of mostnatural landforms are generally under 30 degrees.

Slope vrid elevation data can be obtained, with varying degrees of accuracy,from a variety of re, note sensor imagery other than photography. Much work is current-ly being done on the theory and actual development of a stereo capability forthe moreexotic remote sensii tg systems. As pointed out by Derenyi and Konecny (1966), "stereoimagery is the only ;neans to locate and identify objects properly."

Stereo techniques initially require a highly accurate mathematical deserip-tion -,f the parallax I actors and relief displacement factors involved. This has:not yetbeen well done for Pll sensors. All techniques for determining slope and elevation datamust also employ both verticol and horizontal references.

Various ciectro-optical imaging systems, including television-type systeml,are theoreticaly capable of producing images of good resolution and geometry. Withinlimitations, so,-e height and slope data are probably possible from select, single, video-type images. Generally, however, reliable height and slope data must be extracted fromstcrco imagery produced by these. systems.

T hermal-scanner imagery lacks the definition of photography and television-type, electro-optical systems. Such scanner imagery, however, can have good geometryif stringent internal and external controls are exercised during acquisition. Horizontalgeometry can be especially good in the azimuth or w.,ack direction but is more compli-cated in the scan direction. Stereo imagery can be obtained by overlapping flight linesor by use of a stereo scanner (Derenyi and Koneeny, 1966). Rectification of the imag.cry requires sophisticated instrumentation. The resolution end geometry of IR scannerinmgery (other electro-optical scanner systems also) probably will continue to improvewith future systems utilizing highly sensitive detector arrays and advanced stabilizationsystems.

"'he spatial resolution of imagery generated by passive microwave systemsis generally too poor at present for practical consideration as a means of deriving usefulslope and heighi data.

Since radar is a unique active ranging sstem, elevation and slope data canbe obtained from radar imagery. SLAR imagery, especially, has been widely used as amapping tool. Stereo SLAR mapping techniques are also being currently investigatedand show promise. The best results are obtained when the terrain is viewed from oppo-site sides at the same elevation and look angle (45 degrees being optimum).

114

Because of the generally small scale of radar imagery and limited resolutionand tonal contrasts, slope data from radar imagery are generally restricted to large fea-tufres and to determinatio..s of regional slope. The regional data can he quite useful,howe~er, for dope determinations on large watersheds and for general geomorphic stu

- - dies. The derived data in many instances is comparable to that obtained from topo-:- -. graphic maps prepared from aerial photography.

The various tehniques for obtaining elevation and slope data from radar"imagery are discussed at length by Lewis (1971). These techniques are:

relief displacementradar shadowingradar foreshortening

radar power return.

A variation of the radar-slhadowing technique has been used to make general determina-S.... •tions of re ;ional backslopt in mountainous terrain by noting the de-,ression angle at

which radar shadowing first occurs Lewis aiid Waite (1971; discuss at length the ex-"perimental application of this technique.

Some other attempts at producing stcreo radar. magery include the simul-taneous procurement of radar and IR .;carner imagery (Moore, 1969). The parallax dis-placement is in opposite directions on the two kinds of imagery providing the necessarycriteria for stereo viewing. Pseudo-stereo effects have also been produced by superim-posing positive and negative radar transparencies.

a tHeight and slope data can also be obtained with airborne laser and radar

-• altimeter profilers. These sensoro are discussed in detail under element 313 (Elevation).

315. LANDFORM PROFILE

(a) Definition: A determination of the relief outline of a landform along agiven azimuth.

(b) Interpretation Variables: A discission of landform profile dternminationsfrom remote senor imagery must conbidcr many of the samc factors discubted underthe elements: Area (303), Elevation (313), and Slope (314). The reader is referred tothese discusbionb for additional information -ince the bubject of profile determinationswill be odly briefly treated here.

(c) Remote Sensor Applications: Landform profiles can be dtetermined fromstereo aerial photograph) of bufficiunt resolution and mensurable quality. The techniques,

115

J.

F %1.

skill, and equipment required vary with the type of photography (vertical, oblique,panoramic, etc.), its overall quality, and the accuracy required.

Landform profiles can be obtained also from imagery generated by electro-optical imaging systems. Television-type sensors dre capable of providing quality stereo,imagery from which profile.data can be extracted. The limited spatial resolution 6fthermal IR scanner imagery restricts its usefulness for determining lindform profiles;however, generalized profiles of larger fcatures caA be obtained.

The poor spatia csolution of passive microwave imagery seVerely restrictsits use for profile determinations.

Landform profiles can be obtained from a variety of radar imagery includ-ing SLAR but are generally limited to features of large magnitude.

1he radar terrain profiler-a specialized cbmbination of a radar altimeterand barometric reference device-can provide relatively detailkd profiles of the terrainsurface over which it passes. The laser terrain profiler can perform a similar functionand is capable also of recording detail of the surface roughness of landforms.


301 .1 American Society of Photogrammetry, 1960, Manual of Photo-graphic Interpretation, Banta Publishing Co., Menasha, iWisconsin,868 pp.

4i301-2 American Society of Photogrammetry, 1968, Manual of Color

Aerial Photography, Banta Publishing Co., Menasha, Wisconsin,550 pp.

301-3 Anson, A., 1968, "Developments in Aerial Color Photography foýTerrain Analysis," Photograrnmetric Engineering, Vol. 34, No. 10,pp. 10 4 8 -10 51 .

301-4 Barr, D. J., 1969, "Use of Side looking Airborne Radar (SLAR)Imagery for Engineering Soils Studies," Technical Report 46-TR,,

SU. S. Army Engineer Topographic Laboratories, Fort Belvoir,Virginia.

301-5 Christiansen, R, L,, .1968, "A Distinction between Bedrock andUnconsolidated Deposits on 3-5 Micrometer Infrared imagery of

116

•i•,• ~7 *7 i'• Tr••• ••: •• • • •• •

301-5 the Yellowstone Rhyolite Plateau," Interagency Report NASA-104(cont'd) Prepared by the Geological Survey for NASA, 7 pp.

301-6 Cronin, J. F., Rooney, T. P., Williams, R. S. Jr., Molineux, C. E.,and Bliamptis, E. E., 1968, "Ultraviolet Radiation and the Terrest-tral Surface," Special Report 83, Air Force Cambridge ResearchLaboratories, L. G. Hanscom Field, Bedford, Massachusetts, 3 4 pp.

301-7 Fezer, F., 1971, "Photo Interpretation Applied to Geomorphology-a Review," Photogrammetria, Vol. 27, No. 1, pp. 7-54.

301-8 Flint, R. F., 1 971, Glacial and Quaternary Geology, John Wileyand Sons, New York, 892 pp.

301-9 Frost, R. E., Shepard, J. R., Miles, R. D., Montano, P., Parvis, M.,Mintzer, 0. W., and Johnstone, J. G., 1953, "A Manual on the Air-photo Interpretation of Soils and Rocks for Engineering Purposes,"Purdue University, Lafayette, Indiana.

I 301-10 Hemphill, W. R., 1968, "Application of Ultraviolet Reflectanceand Stimulated Luminescence to the Remote Detection of NaturalMaterials," Interagency Report NASA-121, prepared by the U. S.Geological Survey for NASak, 316 pp.

301-11 Holmes, R. F., 1967, "Engineering Materials and Side-looking Radar,"Photogrammetric Engineering, Vol. 33, No. 7, pp. 767-771,

301•12 Hunter, G. T. and Bird, S. J. G., 1970, "Critical Terrain Analysis,"Photogrammetric Engineering, Vol. 36, No. 9, pp. 939-952.

301-13 Krinov, E. L., 1947, "Spectral Reflectance Properties of NaturalFormations," Aero Methods Labecatory, Academy of SciencesUSSR, Moscow, translated by E. Belkov, 1953, National ResearchCouncil, Canada, TechnicA! Translation TT439.

301-i 4 Lueder, D. R., 1959, Aerial Photographic Interpretation-Principlesand Applications; McGraw-Hlill Book Company, Inc., New York,462 pp.

301-15 Marien, 1t. R., Editor, 1970, "An Evaluation of Airborne Sensorsfor Site Selection Engineering Data Requirements," TechnicalReport AFWL-TR-69-95, Air Force Weapons Laboratory, Air

117

301-15 Force Systems Command, Kirtland Air Force Base, New Mexico,(cont'd) 3 17 pp.

301-16 Molineaux, C. E., 1965, "Multiband Spectral System for Reconnais-sance," Photogrammetric Engineering, Vol. 31, pp. 131-143.

301-17 Neal, J. T., 1965, "Airphoto Characteristics of Playas," in Geology,Mineralogy, and Hydrology, of U. S. Playas, Air Force CambridgeResearch Laboratory, Research Paper 96, pp. 149-176.

301-18 Orr, D. G. and Quick, J. R., 1971, "Construction Materials in DeltaAreas," Photogrammetric Engineering, Vol. 37, No. 4, pp. 337-352.

301-19 Pitkin, J. A., 1968, "Airborne Measurements of Terrestrial Radio-activity as an Aid to Geologic Mapping," U. S. Geological SurveyProfessional Paper 516-F.

301-20 Ray, R., 1960, "Aerial Photographs in Geologic Interpretation andMapping," U. S. Geological Survey Professional Paper 373, 229 pp.

301-21 Reed, R. K. and Rinker. J. N., 1968, "Evaluation of Color TestPhotography for MG I Task 3-A Literature Review," Report (intwo volumes) prepared by the U. S. Army Cold Regions Researchand Engineering Laboratory, Hanover, New Hampshire, for theU. S. Army Engineer Topographic Laboratories, Fort Belvoir,Virginia.

301-22 Sabins, F. F. Jr., 1967, "Infrared Imagery and Geologic Aspects,"Photogramrnmetric Engineering, Vol. 33, No. 7, pp. 743-752.

301-23 Thornbury, W. D., 1954, Principles of Geomorphology, John Wileyand Sons, New York, 618 pp.


303-1 (301-1)

303-2 Amnerican Society of PMotogramnmetry, 1966, Manual of Photogram-metry, Third Editioi, Bana Publishing Co., Menasha, Wisconsin,876 pp. (in two volumes).

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303-3 Avery, T. E., 1968, Interpretation of Aerial Photographs, SecondEdition, i.?urgess Publishing Co., Minneapolis, Mizanesota, 324 pp.

303-4 Derenyi, F. E., and Konecny, G., 1966, "Infrared Scan Geometry,"Photogrammetric EJngineering, Vol. 32, No. 5, pp. 780-792.

303-5 Hoffman, P., 1958, "Photiaram-netric Application of Radar ScopePhotograph," Photogrammetri. Engineering, Vol. 24, No. 5, pp.756-765.

303-6 Hovery, S. T., 1965, "Panoramic Possibilities and Problems,"Photogrammetric Engineering, Vol. 31, No. 4, pp. 727-735.

303-7 Kawachi, D. A., 1966, "Image Geometry of Vertical and ObliquePanoramic Photography," Photogrammetric Engineering, Vol. 32,No. 2, pp. 298-307.

303-8 LeResche, J., 1958, "Analysis of the Panoramic Aerial Photograph,"Photogrammetric Engineering, Vol. 24, No. 5, pp. 772-775.

303-9 (301-20)

303-10 Schweider, W. H., 1968, "Laser Terr.-in Profiler," PhotogrammetricEngineering, Vol. 34, No. 7, pp. 658-664.

303-11 Stewart, R. A., 1960, "Mapping the Foxe Peninsula from AerialElectronic Control," Photogrammetric Engineering, Vol. 26, No. 1,pp. 119-122.

303-12 Tomasegovic, Z., 1968, "Direct Determination of Area DistributionBased upon Topographic Features by Means of the Wild 39 Avio-graph," Photogrammetria, Vol. 23, No. 4, pp. 113-123.

303-13 U. S. Naval Reconnaissance and Technical Support Center, 1967,Image Interpretation Handbook, Vol. 1, Government Printing Office,Washington, D.: C.

303-14 Wong, K. W., 1969, "Geometric Distortions in Television Imageries,"Photogrammetric Engineenng, Vol. 35, No. 5, pp. 493-500.

304-1 (301-1)

119

304-2 (301-2)

304-3 (303-3)

304-4 Barringer, A. R., 1966, "The Use of Multi-parameter Remote Sen-sors as an Important New Tool for Mineral and Water ResourceEvaluation," Proceedings of Fourth Symposium on Remote Sensingof Environment, University of Michigan, pp. 313-325.

304-5 Barringer, A. R., McNeil, J. D., 1969, "PinS~Remote Sensing for Geophysical Applications," Proceedings of

Sixth Symposium on Remote Sensing of Environment, Universityof Michigan, Vol. 1, pp. 617-621.

304-6 Barringer, A. R., and McNeil, J. D., 1971, "E-Phase TM: a NewRemote Setsing Technique for Resistivity Mapping," Proceedings(Summaries) Seventh Symposium on Remote Sensing of Environ-ment, University of Michigan, p. 131.

304-7 Cooper, C. F., 1965, "Snow Cover Measure-,ment," Photogramnmetric

Engineering, Vol, 30, No. 4, pp. 611-619.

304-8 Finnegan, W. J., 1962, "Snow Survey;,ng with Aerial Photography,"Photogrammetric Engineering, Vol. 28, No., 5, pp. 782-790.

304-9 (301-11)

304-10 Hruby, R. J. and Edgerton, A. T., 1971, "Subsurface DiscontinrtyDetection by Microwave Radiometry," Proceeding; (Summaries)Seventh Symposium on Remote Sensing of Environment, Univer-sity of Michigan, p. 24.

304-11 Kennedy, J. M., 1908, "A MNirowave Radiometric Study of BuriedKarst Topography," Geological Soiciety of America Bulletin,, Vol.79, No. 6, pp, 735-742. (See also comments by Richer, K., 1970,G.S.A. Bull., Vol., 81, Feb., pp. 585-588.)

304-12 Leonardo, E. S., 1964, "Capabilities and Limitations of RemoteSensors," Photogrammetrw Engineering, V )1. 30, No. 6. pp.1005-iO11.

120

304-13 Lundien, J. R., 1971, "Swept-frequency Radar Measurements toDetermine Layer Thicknesses," Proceedings Seventh (Sumimaries)Symposium on Remote Sensing of Environment, University ofMichigan, p. 23.

304-14 (301-15)

304-15 Mayhew, G. H., 1964, "Geophysical Data as an Aid to Interpreta-tion of Aerial Photographs," Photogrammetric Engineering, Vol.30, No. 1, pp. 58-63.

304-16 Shields, R. R. and Sopper, W. E., 1969, "An Application of SurfaceGeophysical Techniques to the Study of Watershed Hydrology,"Water Resources Bulletin, Vol. 5, No. 3, pp. 37-50.

304-17 (301-23)

305-1 (301-12)

305-2 Sorem, A. L., 1967, "Principles of Aerial Color Photography,"Paper presented at the 32nd Annual Meeting of the AmericanSociety of Photogrammetry, Washington, D. C., March 1967.

305-3 Rib, H. T, 1968, "Color Measurements," in Manual of Color AerialPhotography, sub-chapter 12, published by the American Society ofPhotogrammetry, Falls Church, Virginia, by George Banta Co.,Menasha, Wisconsin.


307-1 (301-1)

307-2 (301-2)

307-3 (304-5)

307-4 (304-6)

121

307-5 Carr, D. D. and Webb, W. M., 1967, "Sand and Gravel Explorationby Thermal Sensing of Soil," Proceedings of th, Third Forum onGeoloay of Industrial Minerals, The University of Kanas3, Lawrence,

.Special Ditribution 34, State Geological Survey of Kansas, pp. 32-39.I 307-6 Davis, B. R., Lur•dien, J. R., and Williamson, A. N. Jr., 1966,"Feasibility Study of the Use of Radar to Detect Surface andGroundwater," Technical Report 3-727, U. S. Army EngineerWaterways Experiment Station, Vicksburg, Mississippi.

307-7 Deal, L. J., Doyle, J. F., Burson, Z. G., and Fritzsche, A. E., 1971,"Environmental Radiation Surveys and Snow Mass Predictions fromAircraft," Proceedings Seventh Symposium on Remote Sensing ofEnvironment, University of Michigan, Vol. 3. pp. 2193-2197.

307-8 Howe, R. H. L., 1958, "Procedures of Applying Air Photo Interpre-tation in the Location of Groundwater," Photogrammetric Engineer-ing, Vol. 24, No. 1, pp. 3549.

3079-9 (301-13)

307-10 (301-15)

307-11 Myers, V. 1. and Heilman, M., 1969, "Thermal Infrared for SoilTemperature Studies," Photogrammetric Engineering, Vol. 35, No.10, pp. 1024-1032.

307-12 Myers. V. I., 1970, "Remote Sensing for Definng Acquifers in Gla-cial Drift." Proceedings of the Third Annual Earth Resources Pro-gram ReN.,.w, NASA Manned Spacecraft Center, Houston, Texas.Vol. 3, Sec. 48.

307-13 Schmer, F. A., Werner, H, D., and Waltz, F. A., 1970, "Summary--Remote Sensing Soil Moisture Research," Proceedings of the ThirdAnnual Earth Resources Program Review, NASA Manmed Space-craft Center, Houston, Texas, Vol. 3, Sec. 49.

307-14 Stockhoff, E,1 H. and Frost, R. T., 1971. "Polarization of Light Re-flected by Nloist Soils," Proceedings Seventh Symposium on RemoteSensing of Ftovironment, University qf Michigan. Vol. 1, pp. 345-349.,

122

307-15 Wer-mund, 1971, "Remote Sensing for Hydroge~logic Prospectingin Arid Regions," IEEE Transactions on Geoscience Electronics,July 1971.

307-16 Winkler, &. M., 1962, "Moisture Measurements in Glacial Soilsfrom Airphotos," Proceedings Second Symposium on RemoteSensing of Environment, University of Michigan, pp. 156-158.

307-17 Williamson, A. N., 1966, "Laboratory Investigations of the Gamma-ray Spectral Region for Remote Determination of Soil TrafficabilityConditions," Proceedings Fourth Symposium on Remote Sensingof Environment, University of Michigan, pp. 623-635.

308-1 (301-1)

308-2 (304.5)

308-3 (304-6)

308-4 Frost, R. E., 1950, "Evaluation of Soils and Permafrost Conditionr,.in the Territory of Alaska by Means of Aerial Photographs," Report(in two volumes) prepared by the EDgineering Experiment Station,Purdue University for the Office of the Chief of Engineers, AirfieldsBranch, Engineering Division, Military Construction, 112 pp.

308-5 Frost, R. E., 1960, "Aerial Photography in Arctic and SubarcticEngineering," Journal of the Air T'-ansport Division, Proceedingsof ithe American Society of Civil E:tgineers, pp. 27-56.

308-6 Horvath, R., and Lowe, D. S., 1968, "Multispectral Survey in theAiaskan Arctc," Proceedings Fifth Symposium on Remote Sensingof Environment, University of Michigan, pp. 483-496.

£ 308-7 (301-15)

308-8 Muller, S. W., 1947, Permafrost or Permanently Frozen Groundand Related Er? gineering Problems, Edwards Brothers, Ann Arbor,Michigan.

308-9 Stoeckler, E. G., 1948, "identification and Evaluation of AlaskanVegetation from Airphotos with Reference to Soil Moisture and

123

308-9 Permafrost Conditions," Preliminary Report, Department of the(cont'd) Army, Corps of Engineers, St. Paul District, 103 pp.

308-10 Taber, S., 1943, "Perennially Frozen Ground in Alaska: Its Originand History," Bulletin of the Geological Society of America, Vol.54, pp. 1433-1548.

308-11 Williams, P. J., 1968, "Ice Distribution in Permafrost Profiles,"Canadian Journal of Earth Sciences, Vol. 5, No. 6, pp. 1381-1387.

309-1 (301-1)

309-2 Boyer, R. E., and McQueen, J. E., 1964, "Comparison of MappedRock Fractures and Airphoto Linear Features," PhotogrammetricEngineering, Vol. 30, No. 4. pp. 630-635.

309-3 (301-7)

309-4 Fischer, W. A., 1963, "Depiction of Soil-Covered Structures byInfrared Aerial Photography," U. S. Geological Survey ProfessionalPaper 475-B, B67-B70.

309-5 Hackman, R. J., 1965, "Interpretation of Alaskan Post-earthquakePhotographs," Photogrammetric Engineering, Vol. 31, No. 4, pp,604-611.

309-6 Howard, A. D., and Mercado, J., 1970, "Low Sun-angle VerticalPhotography Versus Thermal Infrared Scanning Imagery," Geologi-cal Society of America Bulletin, Vol. 81, (February), pp. 521-524.

309-7 MacDonald, H.: M., Kirk, J. N., and Dellwig, L., F., 1969, "The In-fluence of Radar-look Direction on the Detection of Selected Gec-logical Features," Proceedings, Sixth Symposium on Remote Sens-ing of Environment, University of Michigan, Vol, 1, pp. 637-650.

309-8 Norman, J. W., 1976, "Linear Geological Featwes as an Aid toPhotogeological Research," Photogrammetria, Vol.: 25, No. 2/3,pp. 177-189.

124

309-9 Reeves, R. G., 1969, "Structural Geologic Interpretations fromRadar Imagery," Geological Society of America Bulletin, Vol. 80,No. 11, pp. 2159-2164.

309-10 Sabins, F. F., Jr., 1969, "Thermal Infrared Imagery and Its Appli-cation to Structural Mapping in Southern California," GeologicalSociety of America Bulletin, Vol. 83, No. 3, pp. 397404.

309-11 Trainer, F. W., and Ellison, R. L., 1967, "Fracture Traces in Shenan-doah Valley, Virginia," Photogrammetric Engineering, Vol. 33,

No. 2, pp. 190-200.

309-12 Williams, R. S., Jr., and Ory, T, R., 1967, "Infrared Imagery Mo-saics for Geological Investigations," Photogrammetric Engineering,Vol. 33, No. 12, pp. 1377-1381,

309-13 Wise, D., U., 1967, "A Radar Geology and Pseudo-Geology CrossSection," Photogrammetric Engineering, Vol. 33, No. 7, pp. 752-763.

309-14 Wise, D. U., 1969, "Pseudo-radar Topographic Shadowing for De-tection of Sub-continental Sized Fracture Systems," Sixth Sympo.sium on Remote Sensing of Environment, University of Michigan,Vol. 1, pp. 603-617.

309-15 Woodcock, L., F and Lampton, B. F., 1964, "Measurement ofCrustal Movement by Photogrammetric Methods," Photogrammet-

Snric Engineering, Vol. 30, No. 6 , pp. 912-916.,

310-1 Case, J, B., 1958, "Mapping of Glaciers in Alaska," Photogrammet-ric Engineering, Vol. 24, No. 5, pp. 815.821.

310-2 Department of the Air Force, 1953, "Regional Photo Interpreta-tion Series, Antarctica," AFM 200-30,

310.3 k301-8)

310.4 Konceny, G., 1964, "Glacial Surveys in Western Canada," Photo-grainmetric Engineering, Vol. 30, No. 1, pp. 64-83.

310-5 Leighity. R. D., 1966., Terrain Information from High AltitudeSide-looking Radar Imagery of an Arctic Area," Proceedings of

125

•:• I ,,- i i I ,- .. - o

310-5 the Fourth Symposium on Remote-Sensing of Environment, Uni-(cont'd) versity oi Michigan, pp. 575-597.

310-6 McLerran, J. H., 1964b, "Airborne Crevasse Detection," ThirdSymposium on Remote Sensing of Environment, Univtrsity ofMichigan, pp. 801-802.

310-7 Meier, M. F., Alexander, R. H., and Campbell, W. J., 1966, "Multi-spectral Sensing Tests at South Cascade Glacier, Washington," Pro-ceedings Fourth Symposium on Remote Sensing of Emironment,

pp. 145-171.

310-8 Poulin, A. 0., and Harwood, T. A., 1965, "Infrared Mapping ofGlacier Thermal Anomalies," Canadian Journal of Earth Sciences,Vol. 3, No. 6, pp. 881-885.

310-9 Rinker, J. N., Evans, S., and de Q. Robin, G., 1966, "Remote Ice-Sounding Techniques," Proceedings of the Fourth Symposium onI Remote Sensing of Environment, University of Michigan, AnnArbor, pp. 793-800.

310-10 Scheps, B., 1957, "TERRAINS-Terrain Radar InterpretationStudy-(Arctic areas-Grcenlaiid and Antarctica), report prepared

by the USGS for the US Navy, Antarctic Projects Office.

310.1 Smith, B. T. U., 1967, "Photogeologic Interpretation in Antarctica,"

Phorogrammetric Engineering, Vol. 33, No. 3, pp. 297.300.

" I 310-12 (301-23)

311-1 American Geological Institute, 1960, Glossary of Geology and Re-lated Sciences.' with supplement, second edition, published by theAmerican Geological Institute, Washington, D. C.

311-2 (301-1)

311-3 (301-2)

311.4 Birnie, Richard W., 1971, "Infrared Radiation Thcrinornetry ofGuatemalan Volcanos," Paper presented at the 52nd annual meeting

126

311-4 of t~ie American Geophysical Union, April 12-16, 1971, Washing-(:oit' d) ton, D. C.

31 1-C (301-7)

311-6 Fischer, W. A., Moxham, R. M., Polcyn, F., and Landis, G. H., 1964,"Infrared Surveys of Hawaiian Volcanoes," Science, Vol. 146, pp.733-742.

311-7 Friedman, J. D. and Williams, R. S. Jr., 1968, "Infrared Sensing ofActile Geologic Processes," Proceedings of Fifth Symposium onRemote Sensing of Environmtnt, Univerity of Michigan, pp. 787-820.

311-8 McCue, G. A. and Green, J., 1965, "Pisgah Crater Terrain Analysis,"Photogrammetric Engineering, Vol. 31, pp. 810-821.

311-9 Moxham, R. M. and Alcaraz, A., 1966, "Infrared Surveys at TaalVolcano, Philippines,!` Proceedings Fourth Symposium on RemoteSensing of Environment, University of Michigan, pp. 827-845.

311-10 Naughton, J. J., Derhy, J. V., and Glover, R. R., 1969, "InfraredMcsurements on Volcanic Gas and Fume: Kilauea Eruption,1968," Journal of Geophysical Research, Vol. 74, No. 12, pp.3273-3277.

311-11 Quade, J. G., Chapman, P. E., Brennan, P. A., and Blinn, J. C. III,1970, "Multispectral Remote Sensing of ia Exposed Volcanic Pro-vince," Tech. Memorandum 33453, NASA Jet Propulsion Labora-tory, Pasadena, California, 33 pp,

311-12 Shilin, B. V., Gusev, N. A., Miroshnikov, M. M., and Karizhenski,Ye. Ya., 1969, "Infrared Aerial Survey of the Volcanoes of Kam-chatka," Sixth Symposium on Remote Sensing of Environment,University of Michigan, pp. 175-189.

311-13 (301-23)

312-1 Bishop, D. M., and Stevens, M. F., 1964, "Landslides on LoggedAreas in Southeait Alaska," U. S. Forest Service, Research Paper,NOR-i, 55 pp.

127

31 J2-2 Dishaw, i1. E., 1967, "Massive Landslides," PhotogrammetrI4t Engi-neering. Vol. 33, No. 6, pp. 603-610.

3 12-3 Eckel, E. B., et. al., 1968, "Landslides and Engineering Practice,"Highway Research Board, Special Report 29.

312-4 "309-5)

312-5 Mintzer, 0. W. and Mathur, B. S., 1961, "Report of the Use ofColor Photography in the Study of Engineering Soils and Land-slides (unpublished report), Department of Civil Engineering, TheOhio State University, Columbus, Ohio.

312-6 Poole, D. H., 1969, "Slope Failure Forms: Their IdentificationCharacteristics and Distribution as Depicted by Selected RemoteSensor Returns," Sixth Symposium on Remote Sensing of Environ.inent, University of Michigan, Vol. II, pp. 927-966.

312-7 Sharpe, C. F. S., 1960, Landslides and Related Phenomena, PageantBoOks, Inc., New Jersey, 127 pp.

312-8 Swanston, D. N., 1969, "Mass Wasting in Coastal Alaska," U.S.D.A.Forest Service Research Paper PNW-83, 15 pp.

312-9 Tcrzaghi, Karl, 1960, "Medcanism of Landslides," Geological So-ciety Df America Bulletin, Engineering Geology Volume, November1960, pp. 83-121.

312-10 van Wijk, M. C., 1967, "Photogrammetry Applied to AvalancheStudies," Journal of Glaciology. Vol. 6, No. 48, pp. 9 17-9 35 .

313-1 (301-1)

313-2 (303-2)

1 (303-3)

Batson, R. M., 1967, "Surveyor Spacecraft Televisien Photogram.nictry," Photogrammetric Engineering, Vol. 33, No. 12, pp. 1365-1373.

128

313-5 Dalke, G. W. and McCoy, R. M., 1969, "Regional Slopes with Non-stereo Radar," Photogrammetric Engineering, Vol. 35, No. 5, pp.441446.

313-6 (303-4)

313-7 Fiore, C., 1967, "Side-looking Radar Restitution," Photogram met-ric Engineering, Vol. 33, No. 2, pp. 215-221.

313-8 Graham, L. C., 1971, "Cartographic Applications of SyntheticAperture Radar," Paper presented at American Society of Photo-gammetry meeting, Washington, D. C., March 1971.

3i3-9 (303-5)

313-10 (303-6)

313-11 Jensen, H. and Ruddock, K., 1965, "Applicn:;ons of a Laser Pro-filer to Photogrammetric Problems," Paper presented at meetingof American Society of Photogrammetry, March 1971, Washington,D.C.

313-12 (303-7)

313-13 Konecny, G. and Derenyi, E., 1966, "Grometrical Considerationsfor Mapping from Scan Imagery," Pro~ceedings Fourth Symposiumon Remote Sensing of Environment, University of Michigan, pp.327-338.

313-14 LaPrade, G. L., 1963, "An Analytical and Experimental Study ofStereo for Radar," Photogrammetric Engineering, Vol. 29, pp.296-300.

313-15 Leonardo, E. S., 1963, "Comparison of Imaging Geometry forRadar aikd Camera Photographs," Photogrammetric Engineering,Vol. 29, No. 2, pp. 287-294..

313-16 (303-8)

313-17 Levine, D., 1963, "Principles of Stereoscopic Instrumentation forPPI Photography," Photo'grammetric Engineering, Vol. .29, No. 4,pp. 596-621.

129

I . . . . I I I.ql i • I I . . . . - .. . I -

313-18 Lewis, A. J., 1971, "Geomorphic Evaluation of Radar Imagery ofSouthwitem,.Panama and Northwestern Columbia," Technical Re-port 133-18, Centtr for Research Inc., University of •ansas, 164 pp.

313-19 Lewis, A. J.,.and Waite,'W. P., 1971, "Cum6lative FrequencyCurves of Terrain Slopes from Radar Shadow Frequency," Paperpresented at American Society of Photogrmmetry meeting, Wash-ington, D. C., March 1971.

313-20 Link, L. E., 1969, "Capability of AirLorie Laser Profilometer to

Measure Terrain Roughness," Proceeding-, Sixth Symposium on Re-mote Sensing of Environment, Uriversty of Michigan, pp. 189-196.

313-21 Mdsry, S. E., 1969 "'Analytical Treatment of Stereo Strip Photos,"

Phowrgrammetric Engineering, Vol. 35, N-o. 12, pp. 1255-1263.

313.22 McCoy, R. M., 1967, "An Evaluation of Radar Imagery as a Toolfor Drainage Basin AniIysis," CRES Technical Report 61-31, Uni-versity of Kansas, U. S. Department of Agriculture, 8 pp.

313-23 MacFadyen, D. A., 1962, "A Use of APR for Mapping Control inDifficult Terrain," Photogrammetric Engineering, Vol. 28, No. 5,pp, 735-740. i

313-24 Mo3ssaer, K. E. and Choate, G, A., 1966, "Terrain Slope Estima-tion," Photogrammetric Engineering, Vol. 32, No. 1,'pp. 67-75.

313-25 Moore, R. K., 1969, "Heights from Simultaneous Radar and Infra-red," Photogrammetric Engineering, Vol. 35, No. 7,;pp. 649-651.

313-26 Pryor, W. T. and Watson, J. H.,1966, "Ownistereomeasurer BPR,"

Plhotogramme'iic Engineering, Vol. 32, No. 5, pp. 830-832.

313-27 (301 20)

313-28 Rosenfield, G. H., 1968, "Stereo Radar Techniques," Photogramt-metric Engineering, Vol. 34, No. 6, pp. 586-595.

313-29 (303-10)

313-30 (303-11)

130

313-31 (303-12)

31W-32 (303.13)

313-33 (303-14)

313-34 van der Bent, E. 'h., 1969, "Dip Estimation fo," Photogeology,""[ Photogrammetric Engineering, Vol. 35, No. 12, pp. 1225-1228.



1C13

a 0 X o X X X o4 0 X o XN 9

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12. Explanatoky Notes for Cultural Elemei tflf( Senies).

a. Evaluation of the 400 Series.

401. FOOT TRAIL ALIGNMENT

¾• - (a) Definition: A determination of the position of foot trails. "Foot trail"refers to the trace made by pedestrian, pack animal, or two-wheeled vehicle (bicyele,etc.) traffic over the terrain in a cross-country manner, usually with sufficient frequencyto cause permanent disturbance of such natural features as vegetation or groundconditions.

or." 0 (b) Interpretation Variables: A major environmental condition affec 5ing loca-tion of foot trais from aerial imagery is vegetation. Under dense, closed-canopy forests0(tropical rain forest), it may be impossible to locate trails by aerial means; although itmay be possible to detect segments of trails as they emerge from under the forest cano-py in natural or man-made clearings. Location of foot trails under seasonal forest cano-pies (i.e., monsoon forests, scrub forests, some mid-latitude forests) is easiest, but notalways possible, during the season with least vegetative activity (iry or cold season).Usually, trails are readily located in grassland, desert, and polar or alpine environments.i °-

Larger i:mage scales are required in forested regions than in non-forested. regions. Although n(, specific requirements for determining foot-trail alignment have

been found, it is possible to give the following estimates based on military interpreta-tion handbook dta (rM 30-245). In forested regions, 1:10,000 or larger scale imageryis needed. In non-to,, ebted regions, medium- and small-scale imagery would be adequate(up to about 1:60,000).

< (c) Remote Sensors Applications: Aerial photographic sy stems (Ntrtical mode)yield the most useful images (Sensor B-G) for trail-alignment determinations. Thermal

scanner imagery (8-14) will also provide suitable resolution for this MGI element. Radarand othei sensors that provide in oblique vie; are usually not suitable since they do notprovide the necessary aerial patterns needed to determine trail alignment.

"In general, aerial photography BI, C), D1, and El obtained at a scale of1:40,000 or greater will provide enough data to detect foot-trail alignment.

402. ROAD WIDTH

(a) Definition: Road width its mcasured normal to the road centerline and inU!udes the traveled way and any shoulders.

133

'- "• - 4 -

(b) Interpretation Variables: There are relatively few environmental conditionsimpeding road-width determination. In dense forest regions, the forest canopy may ex-tend over portions of the local roads; and, in regions with snew, roads may be tempo-rarily obscured during winter months.

Image scales needed to determine road width will vary according to the ac-"earay desired. For detailed, accurate measurement, scales greater than 1.5,000 wouldbe needed. Image scales to 1:80,000 may be used (TM 30-2451, but as scale decreases,accuracy decreases.

4(c) Remote Sensor Applications: (Since road-width determination involves

the translation of remote sensor data to quantitative measurements, it is important thatthe data be free of distortions.) A wide range of sensors may be employed, but thephotographic systems would provide the best results. Vertical photography offers theeasiest means, although it is possible to obtain road-width measurements from obliqueand other modes of photography. Group II remote sensors (H-J) and Group III remotesensors (K-M) may be used for rtdatively coarse measurements. Laser profilers wouldseem to offer some potential.

"In photographic imagery, road-width determination is a relatively simplemodes (oblique and panoramic).

403. 1F )AD SURFACE COMPOSITION

- ,(a) Definition: The natural and/or man made materials used for the traveledway and shoulders of a road are classified as follows: dirt (includes gravel and macadam),

0 •brick, wood, concrete, and bituminous.0

(b) Interpretation Variables: As in the caze of MGI element 402 (Road Width),there are few environmental bituations, which would interfere with road-surface coinposi-tion interpretation. Snow cover and forest canopies would offer some hindrance, butthe former is temporary or seasonal and the latter would not likely cover very lengthy

" 0 ,,stretches of road.

Road surface composition may generally be interpreted from large-scaleimagery (1:5,000) to small-scale imagery (about 1:60,000) given excellent image qual-ity of the appropriate type.

(c) Remote Sensor Applications: A number of studies have been completedon evaluating road-surface condition; and, while these studies go beyond determining

134

simple road-surface composition (i.e., pavement condition), they offer some evaluation, f different imagery types but all are of the photographic family of remote sensors.

404. RAILROAD ALIGNMENT

(a) Definition: A determination of the location of railroad, roadbed, and tracks.

(b) interpretation Variables; Environmental factors intcrfering with the inter-prevntionof a railroad right-of-way are extremely limited. Railroad alignments can read-ily be determined due to characteristic patterns of curves and conjunction points as wellas grading accommodations (i.e., absence of steep grades). Temporary obscuration ofiminor, narrow-gauge lines in tropical forest regions may be encountered where forestcanopies hang over the railroad roadbed.

, According to TM 30-245, scale may vary from 1:30,000 to larger scales for& •identification, whereas detailed analysis may require 1:8,000 scale and larger. The latter

figure is, however, not applicable to the task of alignment determination but relates to(7• such determinations as gauge. The value given by TM 30-245 is extremely conservative

since experience has indicated that alignment of railways may be determined from scalesas small as 1:80,000.

(c) Remote, Sensor Applications: There appear to be few limiting factors in7 the application of remote sensors other than that the output presents an image of a

tract of the earth's surface. While all photographic systems can be used wiih ease, it isalso possible to use various scanner type systems including radar.

405. NUMBER OF RAILROAD TRACKS

(a) Definition: A determination of the numLer of pairs of rails on a railroadroadbed.

(b) interpretation Variables: As in the case of element 404 (Railroad Align-ment), the,,e are no serious unvironmental factors which would interfere with a determi-nation of the number of railroad trackb. The printcipal limitation is scale. According toTM 30-245 (1967), minimum scale for detailed interpretation is about 1:8,000.

(c) Remote Sensor Application: This MGI factoi is virtually impossible to as-,ertain from radar-type imagerice; and, hence, photographic iadar systems are the mostvaluable if given a scale as cited above.

135

406. BRIDGE LENGTH

(a) Definition: A measurement of the total length of bridge.

(b) Interpretation Variables: Environmental situations which vould hinder aS&dtermination of budge length are extremely limited. Overhanging vegetation in dense

forest regions may offer some hindranct by obscuring bridge approach areas. As with i

most of the target-type MCI elements (i.e., bridge clear width, area dimensions of build-ings, etc.), edge definition or discrimination is the most important factor in detectionand measurement of the object. The sensor that provides the interpreter with the great-est degree of contrast between the target or object and ts background would, therefore,

Sbe the best sensor. Stale limitations for a reliable determination are about 1:30,000 to1:10,000 according to TYM 30-245.

(c) Remote Sensor Applications: Vertical aerial photography is likely to pro-""7 vide the iuest results, although oblique photography may be more useful since other

MGI s cot.cerning bridges may also be obtained from oblique photography. Bridge-length measurement may be obtained through simple photogrammcrric procedures.

(See Manuai of Photogrammetry, 1966.)

407. BRIDGE CLEAR WIDTH

(a) Definition: A measurement of the distance between bridge supporting• / piers or abutments.

(b) Interpretation Variables: There are virtually no serious obstacles to mea-¢ surement of bridge chcar width. Generally, a reasonably large scale Nvouhl be required

and 1:10,000 is given by the Department of Defense (1967). Photogramrnetric proce-° •dures for analysis of oblique photography would have to be used as outlined in the

American Society of Photogrammetry Manual.

(c) Remote Sensor Applications: The principal tool for the above measure-ment is likely to be photograpi.y; ho,,v.eer, oblique modes are necessary so that bridge

piers and abutments are visible.

408. BRIDGE CLEARANCE

(a) Definition- A measureni mnt of the distance between the floor of a road orrailroad bridge span and the surface of die feiture being bridged.

(b) Interpretation Variables: Sai ie as for ,lenent 407.

136

"L____-A

(c) Remote Sensor Applications: Same as for element 407.

409. AREA OF BUILDINGS

(a) Definition: A measurement of the horizontal surface area covered by abuilding.

(b) Interpretation Variables: As this is most often an element associated withurban areas, there are generally no important hindrances provided by any aspect of theenvironment. Basically, the measurement involves simple geometrical problems con-cerned with areas of various shapes. Scale is an important factor; and, according toTM 30-245 (1967), scales of at least 1:12,500 would be needed for reliable measurement.

(c) Remote Sensor Applications: Generally, vertical aerial photography (ofmost any type) in which scale limitations are not serious is most useful. It is possiblealso to obtain cruder measurements of area from various scanner outputs.

F 410. DENSITY OF BUILDINGS

(a) Definition: A summation of the number of buildings per unit area of landsurface.

(b) Interpretation Variables: This MGI clement involves: (a) a count of indi-vidual buildings, and (b) a measurement of land area. Since this is most likely to be anelement of interest in the analysis of ,,ban areas. there are no important environmental

0 deterrents for this procedure. The task inay become more difficult and, therefore, more

time consuming if the topographic conditions within an urban area are extremely hilly,4 thus making it difficult to assess area. Scales may be extremely small-up to about.- " ' °1:80,000.

(c) Remote Sensor Applications: Most imaging types of remote sensors can beused for this element; however, vertical aerial photography is undoubtedly the simplestto use at any level of interpretation ability.

411. HEIGHT OF BUILDINGS

(a) Definition: A measurement of the maximum height of a building fromI' ground level to rooftop.

(b) lnierpretation Variabks: As in the case of elements 409 and 410, thiselement is likely to be principally of interest in urban situations where environmental

137

limitations are virtually non-existent. In rural areas, trees may provide an obscuringcover for lowresidential-type buildings.

(c) Remote Sensor Applications: Resolution limitations of the other sensors(radar, IR, etc.) make aerial photography (Bi, C1, and D1) the most readily availabletool for building-height measurement. It should be noted, however, that parallax invertical photography may cause obscuration of ground level for buildings lo,.ated awayfrom the principal point of the photography. Extensive work has been done to relate"building height and material to radar reflectivifies with some degree of success. A ratio,

- - ranging from 1-10, of the amounts of energy, transmitted and reflected, has been devel-oped for each type of major building material (i.e., sod through steel). The problemsassociated with discrimination of these energy levels on the radar scope, however, re-quire t.ollateral information before a positive determination of either height or materialcan be made. The use of various profilers (laser, etc.) may be applicable for specificinstances.

412. FUNCTIONS OF BUILDINGS

(a) Definition: A determination of the use, or uses, made of a building classi-fied as follows: residential, industrial, commercial, institutional, recreational, transpor-tational, and storage.

0 .

(b) Interpretafion Variables: There are no serious environmental problemswhich can interfere except where buildings may be very densely packed which wouldobscure exterior wall areas. The experienced interpreter may use other building charac.teristics, however, such as ftrn. and shape and association with other urban or rural fea-

* , tures. Scale is the most critical factor for a detailed classification of the type givenabove end according to TM 30-24.5 (1967), scales of 1:12,500 are required.

(c) Remote Sensor Applications: The above task is most easily accomplishedwith aerial photography, although some scanner types of imagery may also be used witha sacrifice in accuracy of interpretation.

4

413. CONSTRUCTION MATERIALS OF BUILDINGS

(a) Definition: A determination of the composition of exterior walls, roofs,and foundations according to the following classification. weed, thatch, sod, brick, con-

V . crete, stone, and metal.

(b) Interpretation Variables: The only environmental factor that might inter-fere w ith interpreting construction material of buildings is if the buildings are so closelyspaced that their walls cannot be seen; however, a trained intcrpreter way be able to Tsc

138

other criteria related to the previous MGI element (412) to determine constructionmaterial.

Scale is extremely significant and a large scale must be used-preferably onthe order of 1:12,500 or larger (TM 30-245, 1967).

(c) Remote Sensor Applications: Oblique photography would provide thebest overall p rspective for seeing the total building. Color photography is likely toprovide more information than black and white photography. I414. URBAN LAND USE AREA

(a) Definition: A determination of the land area which can be classified asurban (as determined by present classification methods; i.e., U. S. Bureau of Census or

.+++'other standards).

(b) Interpretation Variables: The interpretation of urban land use is a relativelygross determination which takes into consideration some of the previous MCI elementssuch as density of buildings and their functions. There appears to be no serious enviroti-mental limitations for making buch an interpretation except in certain urbar. fringe areaswhich may have some complex intermixture of rural-type land uses among urban-typeland uses. General;zation may, however, be employed to take care of such areas.

Since this MGI factor is a relatively gross and general feature, scale is ofless importance. Image scales smaller than 1:100,000 may even be used; although, thesmaller the scale, the greater is the sacrifice of accuracy in placing the urban/ruralboundary.

(c) Remote Sensor Applications: High-altitude aerial photography of anytype as well as radar or even thermal IR can be used with success. Vertical modes aremore useful than oblique modes since an area measurement must be made.

415. URBAN LAND USE FUNCTION

(a) Defirtition: A determination of the use, or uses, made of tracts of landwithin built-up urban areas classified as follows. residential, industrial, commercial,

institutional, recreation, transportation, and storage.

(b) Interpretation Variables: This MGI factor is closely linked to MCI element412 (Functions of Buildings) and is, therefore, largel) dependent on that interpretation.The same variables apply.

139

i in)(c) Remote Sensor Applications: Same as for MGI element 412 (Functions of

Buildings).

416. RURAL LAND USE AREA

(a) Definition: A determination of the land area which can be classified asrural (as determined by present classification methods, i.e., U. S. Bureau of the Censusor other standards).

(b) Interpretation Variables: Same as for MGI element 414 (Urban Land UseArea).

(e) Remote Sensor Applications: Same as for MGI element 414 (Urban LandUse Area).

417. RURAL LAND USE FUNCTION

(a) Definition: A determination of the use, or uses, made of tracts of ruralland classified as follows: cropland, ,veedland, pasture (and fallow) land, orchards (in-r eluding citrus groves and vineyard), and rural industry.

(b) Interpretation Variables: No significant environmental problems are likelyto be encountered in determining land-use function. Scales may be smaller than forurban land-use functions (MGI element 415). Scales as small as 1:60,000 may be used(Lind, A. 0., 1970).

ri (c) Remote Sensor Applications: Aerial photography seems to be the most

versatile tool for successful interpretation according to the above classification.

418. DAM HEIGHT

'10 ,(a) Definition: A measurement of the height of a water-impounding structuremeasured from the level of the stream, on the downstream side, to the top of thestructure.

(b) Interpretation Variables: The principal significant factor ic scale whichshould be large. Scales of about 1:10,000 (TM 30-245, 0967) are likely to providebest results. The procedure involves simple photogrammetric measurements as outlinedin the American Society of Photogrammetry Manual (1966).

(c) Remote Sensor Application: Stereo aerial photography in the verticalmode or oblique mode would probably provide the best results. However, laser profilers

140

mayr also be used. Radar Les alko I asd to !oczfr. d Z=r~E rbý Er1in most instance-s. these dami, havws bcezi 4rje lzzrc znx1 c~emra ofrd cmrrte. ar2

eel. Small e dams built frLm other =zL-:A l Fu- rW! k t tcOcradar at the presenu time; hencz a "O' h be= Oced in Tz.5• V cz?= 050 M. &ment No references were found on te actuaO of pom.e. fmr 15i,

419. DAM CONSTRMUCION MATER•AL

(a) Definition: A determination of the co siio'n of týe -".tui- according to the fullowing dassificaiam.-o, e too

(b) Interpretation Variables: Same as fI MGI dermeat 413 except !Zvironmental factors would not be significantI

(c) Remote Sensor Applications: Same a for !WGI den•e.• i3 U3 t '•r

Materials of Buildings).

420. DAM FUNCTION

(a) Definition: A determination of the use, or usie, made of an impo,•di=zstructure classified as follows. h) drmlectric pouts, flood control, nW,,o.L•at~e-supply, recreational, or combinations of these.

(b) Interpretation Variables: Environmental factors are not likely to be siz-nificant for interpretation of dam function. Scale is probably the more importaut.and, according to TM 33-245. a scale of about 1:12,500 would provide the requireddata.

(c) Remote Sensor Applications: Comnentional aenral photograph) is likeli tobe most ubefui since other information regardin; damn ib a,, readil) obtained from thL-group of sensor,.


401-1 TM 30-245, 1967, hnage Interpretation Handbook:, Vol. 1, Naval

Reconnaissance and Technical Support Center.

402-1 Amer. Soc. Photogrammetry, 1060, Manual of Photogrammetry.

402-2 Leuder, D. R. (1959), Aerial i'Itotographic Interpretation. Mc(;raw-

Pill.

141

403-1 (402-.)

403-2 American Society Photogr., 1960, Manual of PhotographicInterpretation.

403-3 Wilson, John E., 1969, "Sensor LUetection Capabilities Study,"U. S. Geol. Survey Cire. 616.

403-4 Stoeckelar, E. G., 1968, "Use-of Color Aerial Photography forPavement Evaluation Studies," State of Maine, Materials andResearch Technical Paper 68-6R.

4,03-5 Lind, A. 0., 1970, "An Evaluation of Multiband and Color AerialPhotography for Selected MGI in a Subtropical Desert Environ-ment," USAETL, Tech. Rpt. 54-TR.

404-1 (402-1)

404-2 (403-3)

405-1 (401-1)

406-1 (401-1)

406-2 (402-1)

4,07-1 (402-1)

408 See element 407 for reference.

499-1 (401-1)

410 No references.

142

§ U 411-1 (4,01-1)

• 31.-2 A'very, E., 1968,fnterpretazion of•er-l Phwoograph.. Burgess.

412-1 (4014-)

- 412-2 American Soc. Planning Officials, 1951, "Urban Mapping, AerialPhotography and Duplicating; Some Basic Elements," Information

z14 Rpt. No. 29.ij 413.]1 (-'01-1)

414-1 (412-2)I414-2 Simpson, Robt. B., 1970, "Recognition of Settlement Patterns

A g-ainst a Complex Backaunmd," Dartmouth College ProjectinRemote Sensing (Dept. of 'lcography).

II4-14-3

414-4 Moore. E. G. and Wellar, B. S., 1969, "Urban Data Collection byAirborne Sensor," Journal of the Amer. Inst. of Planners, V. 35.

4i4-5 (,V)3-2)

415-1 See element 412 for referemiec...

1 416 See element 414 for references.

417-1 (403-5)

417-2 Steiner, D-. 1965. "Airphoto Applications for Rural Land UseStudies." Photo grammetria, V. 20. t

417-3 Steiner. D., 1965, "Use of Air Photographs for Inlerp -pting andMapping Rural Land Use in the U. S..' Photogrammetria, V. 20.

143

|I

417-4 Beesch, Hans, and Steiner. D., 1959, "Inteer•tation of LandUtilization from Aerial Photographs," Geographisches Itkstitdt derUniv. Zurich.

418-1 (4111-1) -.

418-2 (402-1)

419 No references.

420-1 (401-1)

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S'-III. DISCUSSION

[ .'.:• •1. -Gener.. The mat cspresentedinVTables-Tthrough V-r, presentthe resultsof -an initial attemp t-t evaluate 20 selected remotesensors for their 4aiity to obtain

- -. data on specific natural.d'eultural terrain compoiients,(81 selected MGI elements).* jToe evaai& rs ,ereeoA-f0i, 2, and X acqerding tolthe fl11oi-ing definitions:

1 0- = failure itbothlevels of-interpreter-ex erience,(extensive giund.data:collection or-other supplmentary data-is required at theI.- present-state-of-the-art).

1 = probable success at the professional level only.2 -probabe succe-s at the Professional and technicdian levels.

I

I X = remote sensor-MGI elemient selection is mr'utually exclusive orincompatible. -

The MQL elements were categorized into four major divisions: (1) Drainageard Water, (2) Vegetation, (3) Landforms and Surficial Materials, and(4) Cultural andIndustrial-Economics. The problems associated with detection of'cach MGI element,recommended interpretation techniques, and the references-pertinent to each evaluation.are presented.

As may be expected, there were numerous problems asscciated with a studyof this type. Most of these could be solved if-the image interpreter, -Dihe sensing systems,and the terrain could be calibrated or if all interpreters had thc,same level of expertisewith all types of imagery, the same degree of understanding of the-natural sciences, andthe same experience with terrain conditions in all areas of the world.

One of the more basic problems was the need to make objective evaluationsrelated-to the art of remote sensing-an art which is highly subjective. To be effective,the evaluations had to consider not only the wide range of environmental effects on theterrain that could either hinder or enhance interpretation but also the human factorsand the quality variations of each image type. The geologist, for example, knowledge-able with limestone formations developed under tropical conditions, would be able torecognize these or similar formations from R.S.I. in any tropical area. If, however, hewere asked to perform the same function in the arctic, he may have difficulty. Lima-

stone in a tropical area has entirely different weathering characteristics from litiestoneformations found in the arctic. Without the aid of image keys or existing geologicalmaps, the inexperienced interpreter is often forced t* make extensive ground surveysbefore his task can be accomplished. The experienice levl or the information training

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of aninterpreter is extrnmely important and cannot be over-emphasized when evaluat-ingR.S.I. as the above example attempts to illustrate.

The MGI elements, as considered in this study, can be divided into two basictypes. The first is the simpler and can usually be obtained directly from the imageryeither by simple observation or with basic photogrammetric measurements. Examplesof this type would include elements 405 (number of RR tracks) apA-409 (area dimen-sions of buildings). These elements can be usually detected by.the technician.!evel in-terpreter. The second type is more complex and contains those ehzments that reqmirea greater degree of experience (profession al-level interpretation). Among the elements,most difficult to determine froxa R.S.I. are those dealing with plant species identifica-tion (elements 208,218,220,222, and 224). This problem crn better be appreciatedwhen it is realized that over 100,000 species of plants are fotind in the tropics aloneand that identification from ground observation is often difficult.

The variability of image quality is also a factor that has to be considered inevaluating RIS.I. for MGI capabilities. In this study, only imagery of the "highestquality" was evaluated. In actual practice, however, the term "quality" is difficult todefine because the quality requirements can vary with the interpretation problem, es-pecially with aerial photography. With some MGI elements, 207 (Tree Height) for ex-ample, low-contrast, flat inmagery is considered to be optimum; while, for element 206(Area of Clearings), high-contrast imagery provides the best data source.

In the earlier stages of this study, it was anticipated that additional informa-tion, sensor development, interpreter training, etc., could be gained by summation ofthe evaluations.5 It now appears, however, that bias in selection of the MGI elementsand the inequalities in the interpretation difficulties of the MGI elements would makethis an unwarranted exercise. "As an example, the 100 series category had the highestpercentage of code 1 eialuations with the landforms, cultural, and vegetation categoriesfollowing in descending order. At the lower level of interpreter experience (code 2),vegetation was the highest foiowed by the cultural elements, landforms, and drainageelements. The high number of code 1. evaluationa attained by the drainage category canpossibly be explained by either the high degree of complexity associated with detectingthe MGI elements in this category or metlr.ds for obtaining information on these ele-ments from R.S.I. being not as well known as those used for some of the other elements.

- Many of the MGI elements were selected with prior knowledge that information waseasily obtainable from R.S.I. Many of the vegetation elements were selected in thismanner probably accounting for the high value of code 2 evaluations in this category.

4 Before any additional information can be acquired from the matrix, the MGI elements

Interim Report, 1969, "A Matrix Evauatico of Rea otz Sensor Capabilities for Militay Geographic Information."

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Would'have to be relisted'according to their complexity-and tioh avaJlabilityofte-"techniques needed, for-their derivation form R.S.I.

As was stated earlier in this report, theevaluations were basedAon thceyeper-ience of the-Ph6tographicJiterpretation Reseafch Division pbrsonnelfand the-availableliteiature. Innimany oftheariticles reviewed, it wadifficpltto separate pre opipni-ifroiwactual:experience; afid, often; the authors-did not'pr6vide ehnughinfoimationto -permit an•MGI/sensor evaluation. The literature did not equally cover- hEl -:sp.t*sfthe-MCI/sens~or field so that 1f& somrie' evaluations th.rei, -was-a surplus of reports while

-for 6thers, especially-those at or near the "state-of-the-aft," therewas little or nod inftr-mation available. 'Thd lack-cdf references available for a given sensor or. MGIddata ele-rnentlls, in itself, a reflection of-the utility, miaturity,-and avaikbility of the varioussensor systems.

IV. CONCLUSIONS

114. Conclusion-s. It ise-66nduded that:

a. 'This study subject is transitory, and a constant updating is necessary tokeep pace -with the rapidly expanding technology in sensor concept, design, and appli-cation. Accumulation of-new information from tests and other sources is a continuousfunction. An update of this report will be considered in 2 years. That update will beb'ased on:

(1) Using actual imagery for evaluation rather than the technical liter-ature (the method used in this study).

(2) Employing large groups of interpreters at both the professional,and technician level to permit statistical evaluation of remote sensor capabilities.

(3) Formulating a matrix for each major climatic zone rather thanone matrix for all climatic zones.

(4) Stratifying MGI elements into groups of equal detection difficultiesand common characteristics.

(5) Employing a more concise breakdown of MGI elements. Some dce-ments, such as Ice Type,(115), were too general.

"(6) Using imagery of known or recognized terrain test areas for evalua-tion, such as the present USAETL Test Site Program.

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-b. Research -is eded todevelop methods and-ttochitiquesfor. derivingqvyantitative terrain iniformnation-from Rý.SI; Evaluation ucriteria for variou~s orms ofR.S.I. miust be developed.

c. Research is needed. with the state-of-the-art and' wit-h' clasaified sensorsto develop the xnsthodsifbr collecting terrain information.

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id dc - dtic · a ., ' tu pio uu l c ie c required-cq ird at -b s "elements of...

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