"International Journal of Geography, Geology and Environment"

Author(s): Manishek Mehra and Shweta Khandelwal

Abstract: The study examines forest-cover dynamics in Dausa District, Rajasthan, over a decade using Landsat‑8 surface reflectance data processed into annual NDVI composites. Its purpose is to develop cloud-free time-series data from 2015 to 2024, classify NDVI values into density‑based categories—very dense, dense, moderate, open and non‑forest—and map spatial-temporal changes in vegetation cover across the district. The authors downloaded and atmospherically corrected multi-temporal Landsat‑8 imagery within Google Earth Engine and applied NDVI calculations using near-infrared and red bands. Annual mean composites were then imported into ArcGIS to classify vegetation densities and assess changes. Results show that mean NDVI values ranged from sparse to dense vegetation, reflecting moderate greenness typical of semi-arid environments. Dense and moderately vegetated areas expanded slightly, while open and degraded scrub categories declined, yielding a net gain of approximately 60 km² of vegetated land between 2015 and 2024. Positive NDVI trends were observed in the southern uplands and eastern piedmont, associated with afforestation efforts and favourable rainfall, whereas negative trends occurred near urban fringes and mining clusters. The findings highlight how rainfall variability, geomorphology and human pressures jointly influence vegetation dynamics, demonstrating the value of remote sensing and GIS in guiding sustainable forest management.

DOI: 10.22271/27067483.2025.v7.i10a.432

Pages: 62-66 | Views: 88 | Downloads: 42

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