A GIS-Based Tree Canopy Analysis and Ground-Level Identification of Tree Species in Basia Block of Gumla District, Jharkhand, India

Mapping tree canopies and identifying species at the species level are important for understanding the health of the ecosystem, vegetation, and biodiversity in the Basia block of Gumla district in Jharkhand, India. This study combines Geographical Information Systems (GIS), remote sensing methods, and field-based identification of tree species to create a full picture of the distribution of tree canopies and the types of trees that make them up. Google Earth Engine (GEE) was used to do supervised canopy density classification and make Normalized Difference Vegetation Index (NDVI) composites. QGIS was used for spatial analysis, segmentation, and map creation. Along with remote sensing analysis, large field surveys were done to physically identify tree species, record canopy characteristics, and gather georeferenced validation points. The combined method made it possible to accurately mark out areas of dense, moderate, and sparse canopy and helped record 40 different types of trees in the study area. The Basia block, which has dry deciduous forests mostly made up of Shorea robusta (Sal), Terminalia tomentosa (Asan), Diospyros melanoxylon (Kendu), and Madhuca indica (Mahua), showed clear spectral differentiation: Shorea robusta had high NDVI values (0.65–0.82), which meant that the canopy was thick. Terminalia tomentosa (0.55–0.70) and Diospyros melanoxylon (0.50–0.68) had moderately thick canopies. The results help us better understand how plants grow and give us important information for managing forests, assessing biodiversity, and planning for long-term resource use.