Characterization Of Sundarban Mangrove Forest For Systematic Assessment Of Radiometric Stability In ISRO’s EOS-04 SAR Data

Synthetic Aperture Radar (SAR) Calibration and Validation ensures the accuracy and reliability of SAR data over time accounting for systematic errors, changes in sensitivity, and other factors that could affect data quality. In order to ascertain periodic validation of EOS-04 SAR data, the case study with Sundarbans Mangroves has been selected to estimate the consistency of categorical radiometric parameters independently and its cross-validation with the well-known homogenous distributed target, Amazon Rain Forest. The methodology used and confidence gained in this study are discussed at length in this paper so that during radiometric evaluation of RISAT series SAR data, Sundarbans can be considered as one of the homogeneous distributed targets and the process can be automated to provide periodic radiometric evaluation and monitoring of SAR system performance.