Effect of digital elevation model resolution on topographic correction of airborne SAR

Topography in high relief mountainous areas may mask the signal variation in airborne Synthetic Aperture Radar (SAR) data caused by soil moisture, surface roughness and vegetation. It also affects the quality of image calibration and registration. Good quality calibration and registration are required for the use of SAR in the estimation of soil water. To address the problem of topographic effects, the widely available standard 30 m x 30 m United States Geological Survey (USGS) Digital Elevation Model(DEM) has been incorporated into SAR calibration and registration programs. The topographic resolution of SAR imagery relative to the USGS DEM was examined by comparing the correlation between incident angle (theta) and SAR backscatter (sigma(0)) in a high resolution DEM (mapped at 1:4800 and 1:600 from aerial photography for two small areas) to that in the USGS DEM (mapped at 1:240<(00)over bar>). We found that SAR resolved topographic features not resolved by the USGS DEM. Filtering and aggregation techniques were applied to reduce speckle, the apparent noise due to small topographic features resolved by SAR but not resolved by the USGS DEM, and the registration error. Increasing the filter window from 3 x 3 to 5 x 5 to 9 x 9 and the cell size from 6 m x 12 m to 30 m x 30 m to 90 m x 90 m, reduced the unexplained variability in backscatter by 50%. However, there was considerable unexplained variability at all levels of filtering and aggregation. Aggregation to 90 m x 90 m cell size resulted in blurred or obscured surface features of hydrological interest. Filtering with a 9 x 9 window and resolution cell size of 30 m x 30 m was found to be optimal in terms of the amount of variability explained and the kinds of landscape features retained. Even after applying filtering and aggregation techniques, the correlation between sigma(0) and theta for the high resolution DEM (r = 0.54) was much better than for the USGS DEM (r = 0.36). Correction functions for the numerical estimation of terrain influence on the backscatter variation in the SAR image were derived using empirical imaging models. Topographic effects on sigma(0) were further reduced in the corrected images. However, even after correction there was considerable unexplained sigma(0) variability, some of which could be attributed to major topographic features. Thus, landscape features other than theta need to be incorporated in topographic correction procedures.