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    IGARSS__RTC.pptx IGARSS__RTC.pptx Presentation Transcript

    • USE OF RADIOMETRIC TERRAIN CORRECTION TO IMPROVE
      POLSAR LAND COVER CLASSIFICATION
      Don Atwood1 and David Small2
      University of Alaska Fairbanks
      University of Zurich, Switzerland
    • Presentation Overview
      • Introduce Boreal Land Cover Classification project
      • Focus on species differentiation in boreal environment
      • Introduce reference data for land cover classification
      • Introduce method of Radiometric Terrain Correction (RTC)
      • Terrain-flattened Gamma Naught Backscatter
      • Perform RTC on polarimetric parameters to address topography
      • Demonstrate synergy of PolSARpro and MapReady Tools
      • Compare results for RTC-corrected and non-corrected classification
      • Characterize optimal classification approach for Interior Alaska
    • Study Region
      Boreal environment of Interior Alaska
      Characterized by:
      • rivers
      • wetlands
      • herbaceous tundra
      • black spruce forests (north facing)
      • birch forests (south facing)
      • low intensity urban areas
    • Land Cover Reference
    • Study Data
      Quad-Pol data selected:
      • ALOS L-band PALSAR
      • 21.5 degree look angle
      • Of April, May, July, and Nov dates,
      July 12 2009 selected
      • Post-thaw
      • Leaf-on
      • Coverage includes Fairbanks and regional roads
      Pauli Image
    • Problem of Topography
      Span (Trace of T3 Matrix) Wishart Segmentation
    • Aγ & γ0
      Aβ & β0
      Aσ & σ0
      Normalized Radar
      Cross Sections
      Sensor
      Nadir
      Let’s compute Normalized Radar Cross Sections
      • for an Ellipsoidal Earth
      • for Topography
      Near
      Far
    • Backscatter Reference Areas
      For an Ellipsoidal Earth
      Relationships between cross sections
      for ellipsoidal surfaces
    • Terrain-flattening
      We need to move beyond the ellipsoidal Earth to the hills and valleys of the Fairbanks region:
      • Address the layover and foreshortening of geometric distortions
      • Correct the radiometric variations associated with topography.
      To improve our radiometry:
      • use local area contributing to backscatter at each location in the SAR scene
    • Terrain-flattening
    • Terrain-flattening
      Solution: Use simulated image to Normalize β0
      X
      Ref.: Small, D., Flattening Gamma: Radiometric Terrain Correction for SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, 13p (in press).
    • Terrain Correction
      in Coastal BC
      Vancouver
      GTC (Sept 2008) Integrated contributing area
      ENVISAT ASAR WSM data courtesy ESA(based on SRTM3)
    • Terrain Correction
      in Coastal BC
      GTC (Sept 2008) Integrated contributing area
      ENVISAT ASAR WSM data courtesy ESA(based on SRTM3)
    • Coastal BC: GTC
      ASAR WSM GTC
    • Coastal BC: RTC
      ASAR WSM RTC
    • Coastal BC: NORLIM
      ASAR WSM NORLIM
    • Coherency Matrix
      Scattering Matrix
      : “Double Bounce”
      : “Single Bounce”
      : “Volume Scattering”
    • Coherency Matrix
      terrain corrected Coherency Matrix
      Area Normalization
      Radiometric Terrain Correctionof Coherency Matrix
      Radiometric Terrain Correction:
      • Scale all matrix elements by Area Normalization
    • But Wait…..
      For a given class, the ratio of Surface, Double Bounce, and Volume scattering components depend on incidence angle
      POLARIMETRIC IMPLICATIONS OF INCIDENCE ANGLE VARIABILITY FOR UAVSAR
      Guritz, Atwood, Chapman, and Hensley
    • Radiometric Terrain Correctionof Coherency Matrix
      Span: No Normalization Span: Terrain-model Normalization
    • Radiometric Terrain Correctionof Coherency Matrix
      Pauli: No Normalization Pauli: Terrain-model Normalization
    • Integration of PolSARpro
      and MapReady
      Ingest PALSAR data Terrain-correct Perform WishartExport to GIS
      Generate T3 with MapReadydecomposition Cluster-busting
      Radiometric correction using area
      Lee Sigma Speckle Filter
      POA compensation
    • Radiometric Terrain Correctionof Coherency Matrix
      Wishart - No Normalization Wishart - Radiometric Correction
    • Radiometric Terrain Correctionof Coherency Matrix
      USGS Reference Wishart– Radiometric Correction
    • Classification Results
      No Normalization USGS Reference RTC
    • Classification Results
      Urban areas missed / Identified as Open Water
    • Classification Results
      Inability to distinguish Mixed Forests and Shrub / Scrub
    • Accuracy Assessment
      No Normalization
    • Accuracy Assessment
      With RTC
    • Accuracy Assessment
      Comparison
      • RTC yields improved accuracy (particularly for Deciduous Forest)
    • Impact of RTC on forest classification
      No Normalization USGS Reference RTC
    • Conclusions
      • In general, PolSAR classification is difficult!
      • Data fusion provides greatest hope for accurate classification results
      • Radiometric variability caused by topography dominates PolSAR classification
      • Area-based RTC offers effective way to “flatten” SAR radiometry
      • RTC of Coherency Matrix shown to improve classification accuracy:
      • Impact most pronounced for Deciduous Forests
      • Although not complete, RTC approach is simple and effective
      • Different scattering mechanisms (SB, DB, Volume) have different sensitivities to topography. RTC does not address this
      • However, RTC is very effective first order correction for segmenting polarimetric data by phenology rather than topography
    • Discussion
      Don Atwood
      dkatwood@alaska.edu
      (907) 474-7380
      Photo Credit: Don Atwood