Don Atwood & David SmallIGARSS July USE OF RADIOMETRIC TERRAIN CORRECTION TO IMPROVE POLSAR LAND COVER CLASSIFICATION USE OF RADIOMETRIC TERRAIN CORRECTION TO IMPROVE POLSAR LAND COVER CLASSIFICATION Don Atwood 1 and David Small 2 1)University of Alaska Fairbanks 2)University of Zurich, Switzerland
Don Atwood & David SmallIGARSS July 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
Don Atwood & David SmallIGARSS July 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
Don Atwood & David SmallIGARSS July Land Cover Reference
Don Atwood & David SmallIGARSS July Study Data Quad-Pol data selected: ALOS L-band PALSAR 21.5 degree look angle Of April, May, July, and Nov dates, July selected Post-thaw Leaf-on Coverage includes Fairbanks and regional roads Pauli Image
Don Atwood & David SmallIGARSS July Problem of Topography Span (Trace of T3 Matrix) Wishart Segmentation
Don Atwood & David SmallIGARSS July Normalized Radar Cross Sections Nadir Sensor Far Near A σ & σ 0 A γ & γ 0 A β & β 0 Let’s compute Normalized Radar Cross Sections for an Ellipsoidal Earth for Topography
Don Atwood & David SmallIGARSS July Relationships between cross sections for ellipsoidal surfaces Backscatter Reference Areas For an Ellipsoidal Earth
Don Atwood & David SmallIGARSS July 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
Don Atwood & David SmallIGARSS July Terrain-flattening Convention12345 Earth ModelNoneEllipsoidTerrain Reference Area Area Derivation Normalisation Product GTC NORLIM RTC
Don Atwood & David SmallIGARSS July Ref.: Small, D., Flattening Gamma: Radiometric Terrain Correction for SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, 13p (in press). Terrain-flattening X Solution: Use simulated image to Normalize β 0
Don Atwood & David SmallIGARSS July Vancouver GTC (Sept 2008)Integrated contributing area ENVISAT ASAR WSM data courtesy ESA(based on SRTM3) Terrain Correction in Coastal BC
Don Atwood & David SmallIGARSS July Terrain Correction in Coastal BC GTC (Sept 2008)Integrated contributing area ENVISAT ASAR WSM data courtesy ESA(based on SRTM3)
Don Atwood & David SmallIGARSS July ASAR WSM GTC Coastal BC: GTC
Don Atwood & David SmallIGARSS July ASAR WSM RTC Coastal BC: RTC
Don Atwood & David SmallIGARSS July ASAR WSM NORLIM Coastal BC: NORLIM
Don Atwood & David SmallIGARSS July Coherency Matrix Scattering Matrix : “Single Bounce” : “Double Bounce” : “Volume Scattering”
Don Atwood & David SmallIGARSS July Radiometric Terrain Correction of Coherency Matrix Radiometric Terrain Correction: Area Normalization terrain corrected Coherency Matrix Coherency Matrix Scale all matrix elements by Area Normalization
Don Atwood & David SmallIGARSS July 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 But Wait…..
Don Atwood & David SmallIGARSS July Radiometric Terrain Correction of Coherency Matrix Span: No Normalization Span: Terrain-model Normalization
Don Atwood & David SmallIGARSS July Radiometric Terrain Correction of Coherency Matrix Pauli: No Normalization Pauli: Terrain-model Normalization
Don Atwood & David SmallIGARSS July Ingest PALSAR data Terrain-correct Perform Wishart Export to GIS Generate T3 with MapReady decomposition Cluster-busting Radiometric correction using area Lee Sigma Speckle Filter POA compensation Integration of PolSARpro and MapReady
Don Atwood & David SmallIGARSS July Radiometric Terrain Correction of Coherency Matrix Wishart - No Normalization Wishart - Radiometric Correction
Don Atwood & David SmallIGARSS July Radiometric Terrain Correction of Coherency Matrix USGS Reference Wishart – Radiometric Correction
Don Atwood & David SmallIGARSS July Classification Results No Normalization USGS Reference RTC
Don Atwood & David SmallIGARSS July Classification Results Urban areas missed / Identified as Open Water
Don Atwood & David SmallIGARSS July Classification Results Inability to distinguish Mixed Forests and Shrub / Scrub
Don Atwood & David SmallIGARSS July Accuracy Assessment No Normalization Open Water Developed Land Barren Land Deciduous Forest Evergreen Forest Mixed Forest Shrub/ Scrub Woody Wetlands Herbaceous Wetlands User Accuracy Open Water % Developed Land % Barren Land NA Deciduous Forest % Evergreen Forest % Mixed Forest NA Shrub/ Scrub NA Woody Wetlands % Herbaceous Wetlands NA Producer Accuracy56%15%0%64%47%0% 76%0%51%
Don Atwood & David SmallIGARSS July Accuracy Assessment With RTC Normalized T3 Open Water Developed Land Barren Land Deciduous Forest Evergreen Forest Mixed Forest Shrub/ Scrub Woody Wetlands Herbaceous Wetlands User Accuracy Open Water % Developed Land % Barren Land NA Deciduous Forest % Evergreen Forest % Mixed Forest NA Shrub/ Scrub NA Woody Wetlands % Herbaceous Wetlands NA Producer Accuracy61%15%0%79%49%0% 72%0%54%
Don Atwood & David SmallIGARSS July Accuracy Assessment Comparison Producer ClassRTCNo RTCImprovement Open Water61%56%5% Developed Land15% 0% Deciduous Forest79%64%15% Evergreen Forest49%47%2% Woody Wetlands72%76%-4% RTC yields improved accuracy (particularly for Deciduous Forest)
Don Atwood & David SmallIGARSS July Impact of RTC on forest classification No Normalization USGS Reference RTC
Don Atwood & David SmallIGARSS July 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
Don Atwood & David SmallIGARSS July Discussion Don Atwood (907) Photo Credit: Don Atwood