Improved alpha angle estimation of polarimetric SAR data. Issue 5 (1st March 2016) - Lu, Da; Zou, Bin
Abstract : Land cover classification is one of the primary applications of remote sensing. Polarimetric synthetic aperture radar provides significant information of scattering mechanism for classification. The alpha angle extracted from the Cloude eigenvector decomposition has been wildly used in discriminating targets. However, the alpha angle is always overestimated in forest area, which will induce misclassification. The estimation bias of alpha angle will be discussed. An improved alpha angle estimation method is introduced to overcome the aforementioned problem. A validation process is performed by using National Aeronautics and Space Administration/Jet Propulsion Laboratory Airborne Synthetic Aperture Radar data.