LULC Mapping using Remote Sensing – Project
Performed data annotation and land use/land cover labeling for remote sensing imagery of Hyderabad. Used machine learning algorithms to classify images from 2019, 2022, and 2024. Generated insights into urban expansion and environmental changes based on labeled data. • Processed multi-year satellite image datasets for accurate mapping. • Annotated and labeled data for land cover classification using Random Forest, CART, and Naive Bayes. • Generated structured datasets for further climate and urban analysis. • Ensured quality control and validation of labeling outputs.