Introduction To Polarimetric SAR - NASA

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National Aeronautics andSpace AdministrationARSETApplied Remote Sensing uction to Polarimetric SARNaiara Pinto – Caltech / Jet Propulsion Laboratorywww.nasa.gov

AcknowledgementsFrom NASA:Bruce ChapmanMichael DenbinaScott HensleyMarco LavalleYunling LouMarc SimardUAVSAR teamArmstrong Flight Research CenterFrom Alaska Satellite Facility:Brian HubertyNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program2

Learning objectives In previous weeks, we learned that radarsignals can interact with the earth’s surface The received signal provides informationabout properties of scatterers on the ground More information is gained by studyingdifferent polarizations Our objective is to provide a briefintroduction to polarimetry and familiarizestudents with:– Mathematical representation– Data format– Data processing for land cover mappingSource: ESA- ASAR HandbookNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program3

Outline1. Why polarimetry?2. Polarization3. Scattering mechanisms4. Data and software5. Process Sentinel-1 dual-pol images6. Process UAVSAR quad-pol images7. Display resultsNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program4

Why polarimetry?

Libreville, GabonAs seen withoptical imagerymud banksopen waterforestdense mangroverunwaybuildingstall mangroveNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program6

Libreville, GabonAs seen with Lband SAR imagerymud banksopen waterforestdense mangroveHH HV VVrunwaybuildingstall mangroveNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program7

Polarization

Polarization Radars produce electromagnetic waves. Thedirection of the electric field lies in the planeperpendicular to the direction of propagationand defines the polarization of the wave. Dual-pol instruments:– Transmit H or V, receive H and Vsimultaneously Quad-pol instruments: The amount of returned signal for differentpolarizations depends on the physics of theinteraction of microwaves with the surface.National Aeronautics and Space Administrationreceive– Transmit H and V on alternate pulses, receiveH and V simultaneouslytransmitHVHHHVHVHVVVApplied Remote Sensing Training Program9

PolarimetryMapping Canadian peatlands: Merchant et al. 2017 Radar polarimetry is the study of usingmultiple polarimetric returns to inferinformation about a surface. Applications include:– Cryosphere– Vegetation– Hydrology Two complementary approaches to studyingpolarimetry:– Theoretical models predict how polarized signalinteracts with different media– Observations made with remote sensinginstruments reveal polarization signatures for arange of land cover typesNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program10

Scattering mechanisms

Scattering mechanisms Quantifying scattering mechanisms starts byencoding the received radar signal in a scatteringmatrix.surface In the quad pol scenario, we can represent thereceived signal with a 3x3 T3 coherency matrix:volume scatter [T] * denotes conjugation and denotes averagingdouble bounce All 9 elements in the T matrix are calculated foreach pixel in your image. We employ polarimetric decompositions to obtain asmall set of parameters to classify scatteringmechanisms.National Aeronautics and Space AdministrationApplied Remote Sensing Training Program12

H-α Decompositionplantation Based on eigenvalue / eigenvectordecomposition of the T3 matrixmangrove Eigenvalues λ are used to calculate entropy,(H) which is a function of noise owing todepolarization.EntropyNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program13

H-α Decomposition Based on eigenvalue / eigenvectordecomposition of the T3 matrix Eingenvectors contain the parameter αwhich represents the dominant scatteringmechanism.Figure from Jagdhuber, Thomas, et al. "Identification of soil freezing and thawing states using SAR polarimetry at C-Band." Remote Sensing 6.3 (2014): 2008-2023.National Aeronautics and Space AdministrationApplied Remote Sensing Training Program14

H-α Classification Two-parameter system used to classifydifferent types of scattering behavior 9 Zones Results from this unsupervisedclassification can be combined withother layers and used as inputs for asupervised classifier. For example: Qi, Zhixin, et al. "A novelalgorithm for land use and land coverclassification using RADARSAT-2polarimetric SAR data." RemoteSensing of Environment118 (2012): 2139.Cloude, Shane R., and Eric Pottier. "An entropy based classification scheme for land applications of polarimetric SAR." IEEE Transactions on Geoscience and Remote Sensing 35.1 (1997): 68-78.National Aeronautics and Space AdministrationApplied Remote Sensing Training Program15

H-α ClassificationHigh entropyLowentropyNational Aeronautics and Space AdministrationMediumentropyApplied Remote Sensing Training Program16

H-α ClassificationMultipleDipole /vegetationSurfaceNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program17

Process Sentinel-1

Sentinel-1 download from Alaska Satellite Facility Spaceborne instrument operated by ESA C band (5-cm wavelength) Two polarizations:– VH– VV GRD (Ground Range Detected) product 10 meters spatial posting Product ID:S1A IW GRDH 1SDV 20160320T050613 20160320T050638 010448 00F805 14D5 Acquired on March 20, 2016 Download the zip filehttps://vertex.daac.asf.alaska.eduNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program19

Sentinel-1 process in SNAPZIP Process following the steps in ARSET tutorial“SAR Processing and Data Analysis” Outputs two files:subset– VV– VHcalibratemultilookgeocodeNational Aeronautics and Space AdministrationGEOTIFFApplied Remote Sensing Training Program20

Process UAVSAR

Uninhabited Aerial Synthetic Aperture Radar (UAVSAR) Airborne instrument operated by NASA L band (24-cm wavelength) Fully polarimetric GRD (Ground Range Detected) product 6 meters postinghttps://uavsar.jpl.nasa.govNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program22

Uninhabited Aerial Synthetic Aperture Radar (UAVSAR) Product ID:Mondah 27080 16015 000 160308 L090 CX 02 Acquired on March 03, 2016 Download all 6 *GRD files as well asannotation file *ANNhttps://uavsar.jpl.nasa.govNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program23

PolSARpro PolSARpro is developed under contract withESA since 2003. The IETR (Institute ofElectronics and Telecommunications ofRennes - UMR CNRS 6164) of the Universityof Rennes 1, France is in charge of thedevelopment of the PolSARpro software. Windows and Linux; it is possible to compile onMacOSX from Linux source files GUI or command line Open source We will show command line routines but anexample practice with GUI is /presentations2015/UAVSAR Workshop2015 Polarimetry Tutorial ownload/version-5.0National Aeronautics and Space AdministrationApplied Remote Sensing Training Program24

PolSARproCommand Linemake quicklooksimport files fromUAVSAR, ALOS, ional Aeronautics and Space AdministrationApplied Remote Sensing Training Program25

PolSARproYou can call any function with no arguments to see the expected inputs#cd to directory Soft/data process sngl./wishart h a alpha classifier.exePolSARPro will warn you about thelack of arguments, then provide theusageNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program26

Ingest UAVSAR files and make a T3 matrixuavsar convert MLC.exe –hf Mondah 27080 16015 000 160308 L090 CX 02.ann\-if1 Mondah 27080 16015 000 160308 L090HHHH CX 02.grd \-if2 Mondah 27080 16015 000 160308 L090HHHV CX 02.grd \input rows and cols-if3 Mondah 27080 16015 000 160308 L090HHVV CX 02.grd \-if4 Mondah 27080 16015 000 160308 L090HVHV CX 02.grd \-if5 Mondah 27080 16015 000 160308 L090HVVV CX 02.grd \-if6 Mondah 27080 16015 000 160308 L090VVVV CX 02.grd \-od T3 -odf T3 -inr 3750 -inc 12618 -ofr 0 -ofc 0 -fnr 3750 -fnc 12618 -nlr 2 -nlc 2 -ssr 1 -ssc 1I called the output directory ‘T3’taking looksNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program27

H-α decomposition and classificationh a alpha decomposition.exe -id T3 -od decomposition -iodf T3 \-nwr 7 -nwc 7 -ofr 0 -ofc 0 -fnr 1875 -fnc 6309 \-fl1 0 -fl2 1 -fl3 1 -fl4 1 -fl5 0 -fl6 0 -fl7 0 -fl8 0 -fl9 0-od is the output directory, I’m calling it ‘decomposition’-id is the input directory with T3 elements, I’m calling it ‘T3’-nwr and nwc is the window size used to calculate coherence (7x7)-fnr and fnc refer to number of rows and cols from config.txt file-lf are flags to indicate the desired output files (alpha, entropy, lambda)h a alpha planes classifier.exe -id decomposition -od classification -ofr 0 -ofc 0 -fnr 1875 -fnc 6309 -hal 1 -han 0-anal 0 -clm Planes H A Alpha ColorMap9.pal-od is the output directory, I’m calling it ‘classification’National Aeronautics and Space AdministrationApplied Remote Sensing Training Program28

Make an ENVI headerENVIdescription { File Imported into ENVI.}samples 6309lines 1875bands 1header offset 0file type ENVI Standarddata type 4interleave bsqsensor type Unknownbyte order 0map info {Geographic Lat/Lon, 1.5000, 1.5000, 9.17956764,0.60482616, 1.1112000000e-04, 1.1112000000e-04, WGS-84,units Degrees}coordinate system string {GEOGCS["GCS WGS 1984",DATUM["D WGS 1984",SPHEROID["WGS h units UnknownNational Aeronautics and Space Administration From PolSARPro config.txt file:– Nrow– Ncol From UAVSAR annotation file:– Center Latitude of Upper Left Pixel of Image– Center Longitude of Upper Left Pixel of Image– Multiply GRD Latitude Pixel Spacing by 2 sincewe took 2 looks: 0.00005556 *2 0.0011112Applied Remote Sensing Training Program29

Display results

SentinelVV VH ayBuildingsForestTallmangroveVV Mar 20-16.0-11.7-0.5-4.5-4.2VH Mean(Mar 20, 08)-19.5-16.5-13-10.9-11.9VV Mar 08-17.0-12.6-0.5-5.6-4.3National Aeronautics and Space AdministrationApplied Remote Sensing Training Program31

Alpha 554246Entropy (H)LambdaNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program32

Low entropy 0 H 1 High lpha (α)3629554246Entropy (H)0.150.670.450.890.79LambdaNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program33

OpenWaterRunwayBuildingsForestTallmangroveAlpha (α)3629554246Entropy 067National Aeronautics and Space AdministrationApplied Remote Sensing Training Program34

Entropy AlphaNational Aeronautics and Space AdministrationApplied Remote Sensing Training Program35

Additional Resources Land Remote Sensing course from the European Space LTC2014 Programme Materials.pdf Polarimetry tutorials accompanying rimetry-tutorial Natural Resources Canada tutorial:http://www.nrcan.gc.ca/node/9579National Aeronautics and Space AdministrationApplied Remote Sensing Training Program36

Thank you!

polarimetric SAR data." Remote Sensing of Environment. 118 (2012): 21-39. Cloude, Shane R., and Eric Pottier. "An entropy based classification scheme for land applications of polarimetric SAR." IEEE Transactio

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