Supervised classification using polarimetric SAR decomposition parameters to detect anomalies on earthen levees
Earthen levees protect large areas of populated and cultivated land from flooding. The potential loss of life and property associated with the catastrophic failure of levees can be great. One type of problem that occurs along these levees which can lead to complete failure during a high water event is slough slides [1]. Using Entropy (H), Anisotropy (A), and alpha (α) parameters, we implemented Wishart supervised classification method for the identification of anomalies on the levee. The effectiveness of the algorithms is demonstrated using quad-polarimetric L-band polarimetric Synthetic Aperture Radar (polSAR) imagery from the NASA Jet Propulsion Laboratory's (JPL's) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the southern USA.