Machine Learning Based Crop Classification with Sentinel-1 Data

Soma Gupta

This study focuses on different machine learning algorithms for crop classification for the region of interest (ROI) in the study area of Kendarapara district, Odisha, for the year 2021 utilizing Sentinel-1 data. The study was performed using Google Earth Engine. The performance of four machine learning techniques Random Forest (RF), Classification and Regression Trees(CART), Gradient Boosting, and Support Vector Machine(SVM) algorithm, for three different crop type classifications, were evaluated. The results demonstrated that CART has the highest accuracy of 98.77%.




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