Segmenting and extracting terrain surface signatures from fully polarimetric multilook SIR-C data

We report results from the segmenting and study of terrain surface signatures of fully polarimetric multilook L-band and C-band SIR-C data. Entropy/alpha/anisotropy decomposition features are available from single multilook pixel data. This eliminates the need to average data from several pixels. Entropy and alpha are utilized in the segmentation along with features we have developed primarily from the eigenanalysis of the Kennaugh matrices of multilook data. We have previously reported on our algorithm for segmenting fully polarimetric single look TerraSAR-X, multilook SIR-C and 7 band Landsat 5 data featuring the iterative application of a feedforward neural network with one hidden layer. A comparison of signatures from simultaneously recorded data at L and C bands is presented. The terrain surfaces surveyed include the ocean, lakes, lake ice, bare ground, desert salt flats, lava beds, vegetation, sand dunes, rough desert surfaces, agricultural and urban areas.