Discrimination of maize crop with hybrid polarimetric RISAT1 data

Abstract

Microwave remote sensing provides an attractive approach to determine the spatial variability of crop characteristics. Synthetic aperture radar (SAR) image data provide unique possibility of acquiring data in all weather conditions. Several studies have used fully polarimetric data for extracting crop information, but it is limited by swath width. This study aimed to delineate maize crop using single date hybrid dual polarimetric Radar Imaging Satellite (RISAT)-1, Fine Resolution Stripmap mode (FRS)-1 data. Raney decomposition technique was used for explaining different scattering mechanisms of maize crop. Supervised classification on the decomposition image discriminated maize crop from other land-cover features. Results were compared with Resourcesat-2, Linear Imaging Self Scanner (LISS)-III optical sensor derived information. Spatial agreement of 91% was achieved between outputs generated from Resourcesat-2, LISS-III sensor and RISAT-1 data.