This Study proposes the approach for crop classification using Grey Level Co-occurrence Matrix feature of Synthetic Aperture Radar (SAR) images. The method utilizes SAR Images acquired by Sentinel 1A Data and extract textural features GLCM. In this study, we investigate potential (GLCM)-based texture information horticulture with images in Kharif cloud weather condition. A study on satellite im...

Synthetic aperture radar (SAR) is a general method for generating high-resolution radar maps from low-resolution aperture data which is based on using the relative motion between the radar antenna and the imaged scene. Originally conceived in the early 1950s [1], it is extensively used to image objects on the surface of the Earth and the planets [2]. A synthetic aperture is formed using electro...

This work introduces an innovative radiometric terrain correction algorithm using PolInSAR imagery for improving forest vertical structure parameter estimation. The variance of radar backscattering caused by terrain undulation has been considered in this research by exploiting an iteration optimization procedure to improve the backscattering estimation for a Synthetic Aperture Radar (SAR) image...