5 May 2016 Urban area mapping from polarimetric SAR data using fuzzy inference system
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In this work, we present urban area mapping from full-polarimetric synthetic aperture radar (SAR) data using fuzzy inference system (FIS). In particular, our aim is to utilize the profound knowledge available about scattering mechanism from urban targets to delineate urban environment. In this approach, we have utilized the recently developed polarimetric SAR scattering power decomposition technique (SD-Y4O) given in Bhattacharya et. al. The improved powers along with some other polarimetric parameters were used in this study. A suitable normalization procedure was adapted to handle the skewness in the estimated parameters. The fuzzy if-then rules were constructed from the in-depth knowledge of scattering mechanisms from an urban environment. Suitable methods were introduced to define the fuzzy inference system. The defuzzified membership values were thresholded using an unsupervised clustering method (k-means). The pixels lying in the range [μmax−σ, μmax+σ] corresponds to urban areas where µmax is the largest cluster center and σ is the standard deviation of the cluster corresponding to µmax. The extracted urban area is in visually good agreement with the high resolution optical image. ALOS PALSAR full-polarimetric L-band SAR data has been used in this study.
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Asmeet Ahluwalia, Asmeet Ahluwalia, Surendar Manickam, Surendar Manickam, Avik Bhattacharya, Avik Bhattacharya, Alok Porwal, Alok Porwal, "Urban area mapping from polarimetric SAR data using fuzzy inference system", Proc. SPIE 9877, Land Surface and Cryosphere Remote Sensing III, 987721 (5 May 2016); doi: 10.1117/12.2223823; https://doi.org/10.1117/12.2223823

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