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A DEMONSTRATION OF ERTS-IANALOG AND DIGITAL TECHNIQUES

APPLIIED TO STRIP MINING IN^MARYLAND AND WIST VIRGINIA

(NAS1-TM-X-7C798) A DEMONSTRATION OP EBTS-1 N75-15133ANALOG AND DIGITAL TECHNIQUES APPLIED TOSTHIP MINING IN MARYLAND AND WEST VIBGIHIA(NASA) 19 p HC $3.25 CSCL 081 Unclas

v G3/43 069 7

^ ARTHUR T:^AN])ERS6lsl ""';

iY

' JANE SCHUBERTReproduced by .

^ NATIONAL TECHNICAL <A INFORMATION SERVICE :.^i US Dopartment ol Commerce / "

Sprinslield, VA. 22151

NOVEMBER 1974

WES SU8JEQ

GODDARD SPACE FLIGHT CENTERGREENBELT, MARYLAND

Fqr infoirmation concerning availabilityof this document contact: . \ "*---^ * ^

•' ^ *^Technical Information Division, Code 250

Goddard Space Flight Center- Greenbelt, Maryland JZ0771

" (Telephone 301-982-M88)

\

"This paper presents the views of .the author (s), and does not necessarilyreflect the views of the Goddard Space. Flight Center, or NASA."

X-923-74-313Preprint

A DEMONSTRATION OF ERTS-1ANALOG AND DIGITAL TECHNIQUES

APPLIED TO STRIP MINING INMARYLAND AND WEST VIRGINIA

Arthur T. AndersonJane Schubert

November 1974

GODDARD SPACE FLIGHT CENTERGreenbelt, Maryland

To be submitted in Photogrammetric Engineering.

A DEMONSTRATION OF ERTS-1 ANALOG AND DIGITAL TECHNIQUESAPPLIED TO STRIP MINING IN MARYLAND AND WEST VIRGINIA

Arthur T. Andersonand

Jane Schubert

ABSTRACT

The largest contour strip mining operations in westernMaryland and West Virginia are located within the GeorgesCreek and the Upper Potomac Basins. These two coalbasins lie within the Georges Creek (Wellersburg) syncline.The disturbed strip mine areas were delineated with thesurrounding geological and vegetation features using ERTS-1data in both analog (imagery) and digital form. The two digi-tal systems used were: (1) the ERTS-Analysis system, apoint-by-point digital analysis of spectral signatures basedon known spectral values, and (2) the LARS Automatic DataProcessing System. The digital techniques being developedwill later be incorporated into a data base for land use plan-ning. These two systems aided in efforts to determine theextent and state of strip mining in this region. Aircraftdata, ground verification information, and geological fieldstudies also aided in the application of ERTS-1 imagery toperform an integrated analysis that assessed the adverseeffects of strip mining. The results indicated that ERTScan both monitor and map the extent of strip mining todetermine immediately the acreage affected and indicatewhere future reclamation and revegetation may be neces-sary.

Preceding page blank

iii

CONTENTS

Page

INTRODUCTION 1

STUDY AREA 2

METHOD 2

DISCUSSION 7

CONCLUSION 12

ACKNOWLEDGMENTS 14

BIBLIOGRAPHY 15

Preceding page blank

ILLUSTRATIONS

Figure Page

1 Outline of the Georges Creek and Upper Potomac 3Basin study area encompassing parts of westernMaryland and West Virginia

2 Geologic interpretation from ERTS-1 MSS band 7imagery from September 7, 1972. Strip mineareas, noted by dark contour lines in the centralarea, lie within the Monongahela-Pottsville groups 5

3 Five sample areas chosen for LARSYS2 clustering analysisand classification, representative of the study area 3

4 ERTS-Analysis output and U-2 photography which wereverified in the field 9

5 Tabulation of results in the study area and a sampleoutput transparency registered to topographic basefor quantitative studies 10

6 LARSYS2 clustering output, showing the outline and delineation ofthe strip mine areas and 12 cluster areas, for sample areas2 and 5 from Figure 3 11

7 LARSYS2 classification output sample, verified with aircraftand field studies, delineating the strip mines (C) and baresoil (reclaimed area) which is open 13

TABLES

Table

1

Page

ERTS MSS Signature Analysis for International BiologicalProgramme (IBP) Vegetation Classes

vi

A DEMONSTRATION OF ERTS-1ANALOG AND DIGITAL TECHNIQUES

APPLIED TO STRIP MINING INMARYLAND AND WEST VIRGINIA

INTRODUCTION

The effective exploitation of mineral resources involves a compromise betweenthe need for the resource and the effects of despoliation on the land caused bystrip mining. For example, coal mining is extremely profitable, and the pro-duct is a needed energy source; but, its effects can be devastating. This pointwas best summarized by Jane Stein (1973). With the improved mechanicalmethods of strip mining, coal is easily available and the percentage of affectedareas is increasing throughout the United States. At this time, 14 states areaffected by strip mining. Emphasis on the discovery of additional deposits hasincreased due to the current energy crisis. Newspapers and magazine articleshave predicted finds of 1400 trillion kg (1. 5 trillion tons) of coal within 1800 m(6000 ft) of the surface. Perhaps more practical is the estimate of 90 trillionkg (100 billion tons) of coal in seams 6 to 76 m (20 to 250 ft) below the surfacethat can quickly be recovered through strip mining techniques. Such possi-bilities are being investigated with the new discoveries of significant amountsof coal such as in Montana, Wyoming, and North Dakota where an area coveringover 8 percent of this tristate region (about half the size of Rhode Island) hasbeen found to contain coal. However, the abundance of coal and the need forthe resource are impacted by national and state regulations to limit the yearlyoutput of coal for ecological reasons: a conflict facing many areas of thenation today.

Looking at this situation in terms of smaller, local, and immediate problems,the area of western Maryland and West Virginia within the Potomac River Basinwas studied using the Earth Resources Technology Satellite (ERTS-1) imageryand digital data. The principal purpose of this experimental study was todemonstrate the utility and application of ERTS-1 data in an integrated analysis,to both map and monitor strip mining, and to develop the needed methods andtechniques to provide a data base for future land use planning. For example,Georges Creek Basin and the Upper Potomac Basin in Garrett and Alleganycounties of western Maryland were examined using both an analog technique(photographic interpretation) and digital analysis. This area is now producingover 90 percent of the 1.45 billion kg (1.6 million tons) of coal mined each yearin Maryland. These two counties are comprised of 3,044.76 km^ (721,376acres). Using aircraft photographs of these same counties, 25.16 km^ (6216acres) were categorized as extractive (strip mines) according to the land useclassification of 1973 by the State Planning Commission. *

*Thomas, E., etal., private communication, 1973.

STUDY AREA

The strip mine study area is outlined on a 1:250,000 scale map (Figure 1). Thearea in western Maryland borders the Garrett/Allegany county boundary fromFrostburg and extends southward, paralleling Georges Creek and North Branchmain-stream-head waters of the Potomac, and ends in Steyer, Maryland. Thisarea is within the great Appalachian coal region which extends from Pennsyl-vania to Alabama. Physiographic ally, the Maryland area encompasses theGeorges Creek Basin to the north and Upper Potomac Basin to the south dividedby the right-angle bend of the Potomac. These two divisions are purely artificialand together constitute a single structural unit of the Georges Creek (Wellers-burg) syncline.

The overall area is a gentle elongated shallow syncline which trends northeast-southwest between Dan's Mountain and the Allegheny front on the east and bothBig Savage and Backbone Mountains to the west. The mountain ranges formthe flanks of the gently dipping syncline within the eastern border region of theAllegheny Plateau and contain geologic formulations of Permian and Pennsylvan-ian age. Located here are the only coal bearing seams in Maryland. The forma-tions are the Dunkard, Monongahela, Conemaugh, Allegheny, and Pottsvillegroups. Although these formations are approximately 518 m (1700 ft) thick,about 18.9 m (62 ft) contain usable coal in seams ranging from 0.3 to 4.3 m(1 to 14 ft) in thickness. Specifically, the major coal seams in this area arethe Pittsburg, Barton, Franklin, and Sewickley seams.

METHOD

During the preliminary examination of strip mine regions, the first step in thisstudy was to demonstrate the utility and application of the ERTS output for amultilevel analysis of immediate problem areas and for future planning of landuse management. With this in mind, it was determined that the use of map-related data, imagery, geologic analysis, and computer processing techniqueswould provide a more accurate and complete assessment of strip mines forboth a total acreage figure and for determining active, inactive, or reclaimedmining areas. It should be noted that strip mines go through various stagesof development and reclamation in a period of three months to one year andthat some inferences (with the assistance of the Maryland Geological Survey)had to be made in projecting backward in time to determine the approximatestage of development in larger mines. In this context, the study used theSeptember 7, 1972 (1046-15301), ERTS imagery. This imagery provided thebest delineation of the strip mines.

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Table 1

ERTS MSS Signature Analysis for InternationalBiological Programme (IBP) Vegetation Classes

(from Schubert and MacLeod, 1973)

CorrectedDigital

Tape Values

0 - 3

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00

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27 - 36

MSS 5 (0. 6 fim to 0. 7 p.m) Reflectance Measurements

55 34 - 50 15 - 34 15

NoVegetation

Water ( • )

Sand-flat inor near water

Sand-flat inor near water

(-)

Bare soil(open

or sandO

Bare soil(open)

or sand

0

Bare soil (open)or sand

O

White beach ordesert sand

(-)

SparseVegetation

(IBP Class 3)

Water ( . )

Scrub oversandIBP-3B

(:)

Scrub oversandIBP-3B

(0

Herbs, grassesover sandIBP-3C

(+)

Herbs, grassesover sandIBP-3C

(+)

OpenVegetation

(IBP Class 2)

Water ( . )

ScrubIBP-2B

ScrubIBP-2B

(;)

Steppe(herbs andgrasses)IBP-2G

(#)

Steppe(herbs andgrasses)IBP-2G

(#)

ClosedVegetation

(IBP Class 1)

Water ( . )

Organicmud-flat

Seasonal shortgrass (orthophyllmarsh)IBP-1M2-2

(M)

Evergreen forest(narrow sclero-phyll) IBP-1A1

(E)

ScrubIBP-1B

(B)

Seasonal grassesIBP-1L2 and 1M2

(G)

Deciduous forestIBP-1A2

(D)

the five sample image enlargement areas chosen from the area of study.These five areas shown in Figure 3 were checked and verified in the field, andthe 12 different spectral signatures were identified. Finally, a multispectralclassification of bands 5 and 7 based on the identified classes was completed,using pattern recognition techniques developed at LARS.

DISCUSSION

The ERTS assessment of the areas affected by strip mining was performed ina two-part analysis through the use of manual image interpretation techniquesand the ERTS-Analysis and LARS computer systems using the CCTs. First,it was found that in using manual techniques with ERTS imagery enlarged to1:125,000 scale, there were limitations due to scale and, consequently, onlythe boundaries of the geologic formations could be defined in relation to thespecific strip mines under investigation. No attempt was made to extractthe total acreage of strip mines. These areas are too small in scale to showthe desired detail with ERTS-1 imagery; they were no more than 80 to 300 m(260 to 1000 ft) across. This technique was not accurate enough for the pur-poses of this study to quantify the entire affected areas by planimetry means,the features being too small. The use of the ERTS computer-compatible tapeswith both the ERTS-Analysis and LARSYS2 systems provided more reliableanswers in the detection and inventory of strip mines. The results of the ERTS-Analysis output can be seen in Figure 4. Results from the computer output werecorrelated with the U-2 photograph; there was excellent size agreement withthe printout. The U-2 photograph was then verified in the field.

Figure 5 presents a compilation of the final results from the ERTS-Analysistechnique in identifying strip mine areas in the two basins using this programand shows a sample output registered to a topographic map. This sample out-put includes the Franklin Hill area which lies northwest of Westernport andoutlines the local strip mines. The analysis, computer time, and statisticallisting, compiled in approximately 8 hours, identified 140 strip mines totaling12. 58 km2 (3109 acres) of disturbed land within the two basins and the adjoiningarea. The stripped, soil covered, and high wall boundaries could be delineatedon the output. The table in Figure 6 also shows the size, number, and percent-age of strip mines in the study area, and it should be noted that the majority ofthe mines are less than 0. 089 km2 (22 acres) in size. In addition, the ERTS-Analysis computer output in transparency form registered to the topographicbase at 1:24, 000 (Figure 5) has already proved to be extremely useful to rec-lamation studies as a rapid method to show the overall extent of the acreageaffected at one specific time, according to James Coffroth of the MarylandGeological Survey (private communication, 1973).

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Figure 3. Five sample areas chosen for LARSYS2 clustering analysis andclassification, representative of the study area.

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(OPEN)

101112

Mluini DataBar* SoilAfrlcultur*AgricultureLow TreesHlfh Tr»«5High Dense Tr*«sHifh D«n» Tr.eiCrast/SpollStrip MinesLow Dense Treesfan

2292205511099236619781319!076«9620323

Figure 6. LARSYS2 clustering output, showing the outline and delineation of thestrip mine areas and 12 cluster areas, for sample areas 2 and 5 from Figure 3.

11

The LARSYS2 multispectral clustering and classification system proved to bevery reliable in detecting and identifying various ground surface conditionsand ground cover of the existing strip mines and vegetation in the study area.The various spectral classes identified in Figures 6 and 7 provide importantland use information for future planning and for incorporation into a usefuldata base. As seen in Figure 6, the 12 clusters of vegetation density and soilcover can be extrapolated spectrally as depicted in the outlined clusteredareas. The sampled areas in Figure 3, areas 2 and 5, outline that area shownin Figure 6. This output from LARSYS2 subdivides the 2.86 km2 (707 acres)(620 pixels) of strip mines (M) in the area (Figure 6). In addition, the classi-fication in Figure 7 resulting from the clustering analysis correlates with thedetailed strip mine state topographic map of the previous ERTS-Analysis out-put. The results of this classification depict the stripped areas (C in Figure 7)and the soil cover overlying the backfilled spoils (open regions in Figure 7).

The analysis of the digital data, compared to manual techniques, proved mostadvantageous in the evaluation of the strip mines. As determined from thecomputer analyses, the reclaimed areas which were grassed over within aperiod of two years or less are somewhat difficult to distinguish from the re-cently recovered and seeded grass regions. This was due mainly to two fac-tors: the spoil material in the reclaimed areas contain a high degree of car-bonaceous content mixed into the original soil cover, and the grass was notdense enough to change the spectral response. Digital computer analysesof affected strip mining areas can be quantitatively examined by applying theadvantages of both systems, ERTS-Analysis and LARSYS2. These data re-duction and interpretation techniques will provide an added tool and rapidmeans of strip mine" assessment.

CONCLUSION

The use of the ERTS-1 data has been shown to provide an immediate applicationin detecting, mapping, and inventorying the effects of strip mining in the UpperPotomac and Georges Creek Basins of Maryland and West Virginia. Thesedata will provide the states with a better means of detecting and monitoringfuture reclamation projects. With the increased needs for fuel, it is estimatedthat the 1.45 billion kg (1.6 million tons) of annual coal production in Marylandwill increase by 10 percent or more in 1974. Through use of the describedmethods, this increase in strip mining can be monitored throughout the dis-turbed regions. Also, at the same time, the progress of backfilled, planted,and reclaimed acreage throughout the state can be monitored, which willresult in a minimum of ecological impact.

12

1.5km0.9 mi

Figure 7. LARSYS2 classification output sample, verified with aircraftand field studies, delineating the strip mines (C) and bare soil reclaimedarea) which is open.

13

ACKNOWLEDGMENTS

The authors wish to express their appreciation to those who assisted andoffered suggestions during the preparation of this paper; in particular, DennisMcFadden, Mike Hoffman, Nick Karlow, James Coffroth, and Dr. HasanAl-Abbas were most helpful.

14

BIBLIOGRAPHY

Jokes, Harold E., "Geography and Geology of Maryland," Maryland GeologicalSurvey, Bulletin #19, 1968, (Revised) pp. 105-111.

Josephy, Alvin M., Jr., "Plundered West: Coal is the Prize, " WashingtonPost, August 26, 1973, pp. C-l, 6.

Maryland Bureau of Mines, "Strip Mining Laws of the State of Maryland,"Bureau of Mines Publication, 1971, pp. 1-10.

Schubert, J. S., and MacLeod, N.H., "ERTS-Analysis, A Remotely AccessedComputer System for Analysis of ERTS Data," NASA Contract Report NAS5-21892, June 1973, p. 29.

Stein, Jane, "Coal is Cheap, Hated, Abundant, Filthy, Needed," SmithsonianMagazine, Vol. 3, No. 11, 1973, pp. 19-26.

Toenges, Albert L., et al., "Investigation of Lower Coal Beds in GeorgesCreek and North Part of Upper Potomac Basin, Allegany and Garrett Counties,Md.,M U.S. D.I. Technical Paper 725, 1949, pp. 1-28.

15