Archives of Current Research International

Forest Canopy Density (FCD) is an important indicator for assessing forest health, biomass distribution, and ecosystem resilience. However, spatially explicit assessments of canopy density in fragmented dry deciduous landscapes remain limited, particularly using integrated multi-index geospatial approaches. This study aims to model forest canopy density in Hunsur Taluk, Mysuru District, Karnataka, India, using multispectral remote sensing data and GIS techniques. Sentinel-2 Level-2A surface reflectance imagery was processed in Google Earth Engine to derive key spectral indices, including the Normalised Difference Vegetation Index (NDVI), Advanced Vegetation Index (AVI), Bareness Index (BI), and Shadow Index (SI). These indices were integrated through a weighted overlay method to generate the final FCD map and classify canopy density into five categories. Land Use/Land Cover analysis revealed that cropland dominates the region (46.60%), followed by scrub forest (18.00%), natural forest (17.21%), and plantations (9.29%). NDVI values ranged from −0.517 to 0.888, while the computed FCD values varied from 7.49 to 80.75, indicating considerable spatial heterogeneity in canopy structure. Low canopy density occupied the largest area (23.23%), whereas very high canopy density accounted for 19.83%, highlighting the presence of dense forest pockets within a predominantly agrarian landscape. The integration of multiple spectral indices improved canopy discrimination and reduced single-index limitations in dry deciduous ecosystems. Overall, the study demonstrates that geospatial FCD modelling provides a reliable and cost-effective framework for forest monitoring and can support sustainable forest management, biodiversity conservation, and environmental planning in semi-arid tropical regions.