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  1. 1. USE OF RADIOMETRIC TERRAIN CORRECTION TO IMPROVE <br />POLSAR LAND COVER CLASSIFICATION <br />Don Atwood1 and David Small2<br />University of Alaska Fairbanks<br />University of Zurich, Switzerland<br />
  2. 2. Presentation Overview<br /><ul><li>Introduce Boreal Land Cover Classification project
  3. 3. Focus on species differentiation in boreal environment
  4. 4. Introduce reference data for land cover classification
  5. 5. Introduce method of Radiometric Terrain Correction (RTC)
  6. 6. Terrain-flattened Gamma Naught Backscatter
  7. 7. Perform RTC on polarimetric parameters to address topography
  8. 8. Demonstrate synergy of PolSARpro and MapReady Tools
  9. 9. Compare results for RTC-corrected and non-corrected classification
  10. 10. Characterize optimal classification approach for Interior Alaska</li></li></ul><li>Study Region<br />Boreal environment of Interior Alaska <br />Characterized by:<br /><ul><li> rivers
  11. 11. wetlands
  12. 12. herbaceous tundra
  13. 13. black spruce forests (north facing)
  14. 14. birch forests (south facing)
  15. 15. low intensity urban areas</li></li></ul><li>Land Cover Reference <br />
  16. 16. Study Data<br />Quad-Pol data selected:<br /><ul><li> ALOS L-band PALSAR
  17. 17. 21.5 degree look angle
  18. 18. Of April, May, July, and Nov dates, </li></ul>July 12 2009 selected <br /><ul><li> Post-thaw
  19. 19. Leaf-on
  20. 20. Coverage includes Fairbanks and regional roads</li></ul>Pauli Image<br />
  21. 21. Problem of Topography<br />Span (Trace of T3 Matrix) Wishart Segmentation<br />
  22. 22. Aγ & γ0<br />Aβ & β0<br />Aσ & σ0<br />Normalized Radar<br /> Cross Sections<br />Sensor<br />Nadir<br />Let’s compute Normalized Radar Cross Sections<br /><ul><li>for an Ellipsoidal Earth
  23. 23. for Topography</li></ul>Near<br />Far<br />
  24. 24. Backscatter Reference Areas<br />For an Ellipsoidal Earth<br />Relationships between cross sections <br />for ellipsoidal surfaces<br />
  25. 25. Terrain-flattening <br />We need to move beyond the ellipsoidal Earth to the hills and valleys of the Fairbanks region:<br /><ul><li>Address the layover and foreshortening of geometric distortions
  26. 26. Correct the radiometric variations associated with topography.</li></ul>To improve our radiometry:<br /><ul><li>use local area contributing to backscatter at each location in the SAR scene</li></li></ul><li>Terrain-flattening <br />
  27. 27. Terrain-flattening <br />Solution: Use simulated image to Normalize β0<br />X<br />Ref.: Small, D., Flattening Gamma: Radiometric Terrain Correction for SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, 13p (in press).<br />
  28. 28. Terrain Correction<br />in Coastal BC <br />Vancouver<br />GTC (Sept 2008) Integrated contributing area <br />ENVISAT ASAR WSM data courtesy ESA(based on SRTM3)<br />
  29. 29. Terrain Correction<br />in Coastal BC <br />GTC (Sept 2008) Integrated contributing area <br />ENVISAT ASAR WSM data courtesy ESA(based on SRTM3)<br />
  30. 30. Coastal BC: GTC<br />ASAR WSM GTC<br />
  31. 31. Coastal BC: RTC<br />ASAR WSM RTC<br />
  32. 32. Coastal BC: NORLIM<br />ASAR WSM NORLIM<br />
  33. 33. Coherency Matrix<br />Scattering Matrix<br />: “Double Bounce”<br />: “Single Bounce”<br />: “Volume Scattering”<br />
  34. 34. Coherency Matrix<br />terrain corrected Coherency Matrix<br />Area Normalization<br />Radiometric Terrain Correctionof Coherency Matrix<br />Radiometric Terrain Correction:<br /><ul><li>Scale all matrix elements by Area Normalization</li></li></ul><li>But Wait…..<br />For a given class, the ratio of Surface, Double Bounce, and Volume scattering components depend on incidence angle<br />POLARIMETRIC IMPLICATIONS OF INCIDENCE ANGLE VARIABILITY FOR UAVSAR<br />Guritz, Atwood, Chapman, and Hensley<br />
  35. 35. Radiometric Terrain Correctionof Coherency Matrix<br />Span: No Normalization Span: Terrain-model Normalization<br />
  36. 36. Radiometric Terrain Correctionof Coherency Matrix<br />Pauli: No Normalization Pauli: Terrain-model Normalization<br />
  37. 37. Integration of PolSARpro <br />and MapReady<br />Ingest PALSAR data Terrain-correct Perform WishartExport to GIS <br />Generate T3 with MapReadydecomposition Cluster-busting<br />Radiometric correction using area<br />Lee Sigma Speckle Filter<br />POA compensation <br />
  38. 38. Radiometric Terrain Correctionof Coherency Matrix<br />Wishart - No Normalization Wishart - Radiometric Correction<br />
  39. 39. Radiometric Terrain Correctionof Coherency Matrix<br />USGS Reference Wishart– Radiometric Correction<br />
  40. 40. Classification Results<br />No Normalization USGS Reference RTC<br />
  41. 41. Classification Results<br />Urban areas missed / Identified as Open Water <br />
  42. 42. Classification Results<br />Inability to distinguish Mixed Forests and Shrub / Scrub<br />
  43. 43. Accuracy Assessment<br />No Normalization<br />
  44. 44. Accuracy Assessment<br />With RTC<br />
  45. 45. Accuracy Assessment<br />Comparison<br /><ul><li> RTC yields improved accuracy (particularly for Deciduous Forest)</li></li></ul><li>Impact of RTC on forest classification<br />No Normalization USGS Reference RTC<br />
  46. 46. Conclusions<br /><ul><li>In general, PolSAR classification is difficult!
  47. 47. Data fusion provides greatest hope for accurate classification results
  48. 48. Radiometric variability caused by topography dominates PolSAR classification
  49. 49. Area-based RTC offers effective way to “flatten” SAR radiometry
  50. 50. RTC of Coherency Matrix shown to improve classification accuracy:
  51. 51. Impact most pronounced for Deciduous Forests
  52. 52. Although not complete, RTC approach is simple and effective
  53. 53. Different scattering mechanisms (SB, DB, Volume) have different sensitivities to topography. RTC does not address this
  54. 54. However, RTC is very effective first order correction for segmenting polarimetric data by phenology rather than topography</li></li></ul><li>Discussion<br />Don Atwood<br />dkatwood@alaska.edu<br />(907) 474-7380<br />Photo Credit: Don Atwood<br />