330 likes | 348 Views
USE OF RADIOMETRIC TERRAIN CORRECTION TO IMPROVE POLSAR LAND COVER CLASSIFICATION. Don Atwood 1 and David Small 2 University of Alaska Fairbanks University of Zurich, Switzerland. Presentation Overview. Introduce Boreal Land Cover Classification project
E N D
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
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
Aβ & β0 Aγ & γ0 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 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