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https://ntrs.nasa.gov/search.jsp?R=20100021233 2018-06-22T23:36:49+00:00Z

Primary Goal• Provide resource managers with remote sensing products that

support ecosystem forecasting models requiring salinity andinundation data.

• Work supports the habitat-switching modules in the CoastalLouisiana Ecosystem Assessment and Restoration (CLEAR) model,which provides scientific evaluation for restoration management(Visser et al., 2008).

Visser, J.M., C. Kaiser, and A.B. Owens. 2008. Forecasting 50-years of Habitat Switching in Coastal Louisiana: No Increased Action & Preliminary DraftMaster Plan. Chapter 4 in: R.R. Twilley (ed.), Coastal Louisiana Ecosystem Assessment & Restoration (CLEAR) Program: A tool to support coastalrestoration. Volume IV. Final Report to Department of Natural Resources, Coastal Restoration Division, Baton Rouge, LA. Contract No. 2512-06-02.

2

Project Description

• Daily MODIS time series are used to generate vegetation,water, and soil indices.

• Daily indices are used to compute percent flooding overany period of time and will be validated with a Iidar DigitalElevation Model.

• Higher resolution data (e.g., Landsat) are used to computesalinity indirectly using CRMS ground truth and modeling.

• Percent inundation and salinity are merged to produce datafor models like CLEAR Habitat Switching Model for coastalmarshes.

GOMA Relationship

• Ecosystem Integration and Assessment

— EIA-2: Data gap analysis and acquisition insupport of resource management

— EIA-3: Develop a Gulf of Mexico Ocean andCoastal Mapping and Monitoring Master Plan

— EIA-4: Implementation of the Coastal and MarineEcological Classification Standard (CMECS) in theGulf of Mexico

• Coastal Community Resilience

Potential Partners/Collaborators

• USGS National Wetlands Research Center-CRMS(Coastwide Reference Monitoring System)

• Barataria Terrebonne National Estuary Program

• Louisiana Dept. of Natural Resources (LDNR)

• NOAA Fisheries Service

Related Proposals

Monitoring Coastal Marshes for PersistentFlooding and Salinity Stress (Radaremphasis) submitted 10/2008 underROSES A:28 Gulf of Mexico by: Kalcic(SSAI); Hall (NASA); Steyer (USGS)

— Assess risks to natural environment 1 g

Habitat Switching Algorithm

!Upland Swamp forest

Fresh marsh

water rnars

water

Brackish rnars6*

ISaline marsh

^:=- fiend changein uridati onsaliniN,

from URL: http://www.clear.Isu.edu/habitat switching/

• 390 Stations across Coastal Louisiana

Measurements include:

• Hydrologywater level, temperature, specificconductance, and salinity

• Accretion data• Forested Swamp Vegetation Data• Herbaceous Marsh Vegetation Data• Soil Properties

wet & dry soil pH, soil-specific conductance,soil salinity, soil moisture content, bulkdensity, percent organic matter, and wet & dryvolume

• Surface Elevation

Coastwide Reference Monitoring System (CRMS)

Data available at http://www.lacoast.gov/crms2/Home.aspx5

Hurricane Rita

,4Z

NASA Time Series Product Tool

• NASA SSC developed the Time Series Product Tool (TSPT) to derivedaily normalized difference vegetation index (NDVI) values from theModerate Resolution Imaging Spectroradiometer (MODIS) Aqua/Terrasatellite data.

NDVI values for patch of marsh over years 2000-2007

NDVI time series weredeveloped daily foryears 2000-2007.

In addition to NDVI,TSPT computes thenormalized differencewater and soil indices(NDWI and NDSI,respectively).

0.35

0.3

0.250aD

0.2

z 0.15

0.10CL

0.05

0

-0.050

Preliminary Estimates of Annual Percent Inundation from MODIS NDVI2003

Pct. lime flooded between Jan.01,2001 and Dec.31,2DD1 thr-0.2 Pct. lime Flooded between Jan.01,2002 and Dec.31,2002 thr-0.2 Pct. lime Flooded between Jan.01,2003 and Dec.31,2003 thr-0.2.. 100% 30.2 ................. ............................... 100°la 30.2 ... 100%

°30.1 ........._.. •....;,q .......:........ ,80°1 30.1 ... _ ;i..... ° 30.1 ... ..... .....80°f 30!

29.9 ; ^}SD%

29.9 +_g ''r`50%

29.9 Aye 4 -SD%

1fbf;^ 40% 40% 40%

29.8T - -..¢"•w'1 .. ° ` 30 °la 29 $ -:.^ . r ^ 30 90 29.$ .1

30 %

° M% 20% 20%

29.7 10% 29.7 - 10% 297 ` - 10%

-93.8 -93.7 -93.6 -93.5 -93.4 -93.3 -93.2 -93.8 -93.7 -93.6 -93.5 -93.4 -93.3 -93.2 -93.8 -93.7 -93.6 -93.5 -93.4 -93.3 -93.2

2001 2002 2003 Pct. time flooded between Jan.01 ,2004 and Dec.31 ,2004 thr-0.230.2 -............ ............................. . ....... 100%

Sabine-Calcasieu Basin Flooding9 30.1

:- ` =.. .a

90%8p

200430.. `" ..

60%

29.9rL{ 'may 4=.''^!^ ^ _

50%401

- 29.8 ............... ... :3G %;G e

29.7 101

-918 -937 -93.6 -93.5 -93.4 -933 -93.2

2007 +M - 20052006Pct. time Flooded between Jan.01,2007 and Dec.31,2007 thr-0.2

30.2 .. e oo e between an an ec Pct, time flooded between Jan.01,2006 and Dec.31,2006 thr- . time0.2 Pct -1D0k 30.2 ............................................. - .. 100°! 30.2 1 100%9D9 90 0/

°90%

......:........"......30.1 .. 30 30 -1 lre 4' ^kY^ i

3 _709

60' 30

f

X60%70°!° ^+

_ a 4

70%60%

i29.9

509

29.91

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50- 4D"

29.8 ic'.4 t ".30 1i 29.8 r ?r' .+ i . 30°l° :

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209 ,.r

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29.7 101) 29.7 10% 29.; 10%

-933 -93.7 -93.6 -93.5 -93.4 -93.3 -93.2 -93.8 -93.7 -93.6 -93.5 -93.4 -93.3 -93.2 -93.8 -93.7 -93.6 -93.5 -93.4 -93.3 -93.27

2005

Coastal Restoration Monitoring Station CS20-15R

Monitoring Station CS20-15RMeasurements at 11:00 CST (MODIS overflight)

4.5

4

3.5

R_ ita

3

2.5

2 I DEM ground elevation = 1.9 ft.

1.5

1

0.5

0 JL Flooded811/05 8/31/05 9/30/05

Landsat NDW I October 31, 2005Mud Lake, Sabine-Calcasieu Study Area

Flooding determined from comparison of DEM from lidar (NAVD88)and gridded water levels from Coastal Restoration MonitoringStation Field Data (NAVD88) for dates shown below.

Comparison to Landsat NDWI values for October 31, 2005, showsless flooding in the image. Further work to calibrate water levels tomarsh elevation is planned as well as more comparison sites.

HurricaneRita

Sept. 24, 2005

0

Sept. 21, 2005 Sept 29, 2005 Oct. 31, 2005 ''' Nov. 24, 2005 'Dec. 26, 2005PA

^ ,xMS * csxu ♦ uxr * c;sal

EIeVdI1011

=<.,o =05 . 1 =2d-1,250 to 20 25_-- l Q_ro.0-10-15-25-, -'.o . t5 QS•-a0

=0.0.5-35.2 =3.0-5 =15.20=30.35• C502 n M23 + C532 = 51uM MBe* -:2a * csal

Elavalion

^<.1a dos -1 O 2a - zs^so - l0 ®2a - z5

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Elevation

U^-10 -05-1 =i0-15-50-10rX:25=.lo.o -LS^xSa CIO. 1s Qn-ao=0 . 06-352 =30 . 5 -1920 Q30-3s

10

Elevation

o ,o.9 ^,a.,5 X25-9 ..9. ,5 =r,. aB=o.os^+5-s ^3o-s X15.2oQw-as

CP.MS * C520 ♦ GSD * C531=sma a<aa

Second Quarter 2006 (April — June)

Mean Salinity

0.05 Prash'svY phi: 'i?a:^F'i

0.6 . 25 01, haina l F

- 2.5 . 5000h io.2 ^*5-]5 MBSO3ah 7.6 toM d11n02

_ 10 . 12.0 Me halna3_ 12.0 - IS MBSOBa3nB L

1 S- I B PJlyhaline I_ 18-21 Polyheline2

PCyhdhe] II

_ 24-27P yhense4 ^4119F

• CP.MS ^ CSdI ♦ C32i =SNtl/Frea^w02 n (623 * (S3f

First Quarter 2006 (January — March)

Mean salinity

0.5-2501gha'Inas_ 2.5. 6 MOM-

hairPl

? r - a

5-]5Mesohatlnel ♦0 `I^3.B33 4''^].5-10 Mxehaline210-125Meso ^^`^:

i)

_ 12 5 . 15 f.Aes0hain0 L <.

15- IBPOlyflallne 1 ^ </0^

_ 18-21 POyhalhe2 -^ a a21- 24 P.hhalhe 3

_ 24- 27 PotiNlhe d ,I^ K4 sn]x • Bsn • 9L•li

^43 *t• ^l

Fourth Quarter 2004 (October — December)

Mean Salinity 4a

O 5-25 Jlghalne l-2.5-S 019NAma2

5-]S Mesohatlne I t 0 'f -- 'h#1.5. 10 Meaohallne 2

9 I r

E . 10-125 Me Bhaln+S

26 . 15Me.Oha- —..-3riF.`' ,5? - n :: ^.•^1

M 1 15- IaPyhalhe l.,,,

_ I8-21 Pot-l'na2 €'

[ 21-24 Pot/Mfloe3

_ 24- 27 PBIyllalhe 4 1 +

Fourth Quarter 2005 (October — December)Mean Salinity

0.05R.S 'x A01-25010loMm I I

1 W __- 1.5-5019ha11. - ^^[_-

^ 1

9 . 75 Mash 1 I ^ ^^ ai

^.^R:i.5-10 Me t I' 210-1:9MB5o0alna3 ' '01.1

- 12.5- 5Mes05a lne4 C,

^el15- 10 POl,halhe 1 _

_ le- 21 Polyhelne 2 `6a21-2i POIrhelhe5

w ^

-2L-2]POlyhelha4^A.tS ^ f

1a•1556

111^^^ 1• 1h+`,I ^ ^y

• Porewater salinity maps forSabine Basin 2005,estimates made fromLandsat 7 (10131/2005)using Neural net, rms=0.09

• Salinities range from 0-18ppt where brighter areasindicate higher salinity

11

Superimposed File Ov rl^ En de ov r law n

Landsat Images-A '^' x

of Normalized iArea before ^` Area after

Difference ^ ^ , N_

Indices Hurricane Rita t *- Hurricane Rita1NDVI — GreenNDWI — Blue

N DS I - Red ' a a_ r {„_

s .Horizontal ,^.,?; •

profile line 7Y , * qj Marshj!^►« Shears

Plots show each index * ialong horizontal profile

line (above), before r(left), and after (right)^$+^ .^

Hurricane Rita.64

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F- I ; ,,, , File Edit options PlotFunckion HelpPre-Rita profile shows

vegetation dominantcover type as

indicated bydominance of NDVI

(green),- post-Ritashows diminished

NDVI and increasedwater index, NDWI

(blue).

r.

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Horizontal Profile

File Edit Options Plot—Function Help

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• Ongoing work to validate flooding with radar (NWRC/USGS) and

enhance persistence estimates through "fusion" of MODIS and

Landsat time series (ROSES A.28 Gulf of Mexico).

• Additional work will also investigate relationship between saltwater

dielectric constant and radar returns (Radarsat) (ROSES A.28 Gulf

of Mexico).

Participation in this work by Science Systems and Applications, Inc., was supported by NASA at the John C. Stennis SpaceCenter, Mississippi, under Task Order NNSO4AB54 15