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Research Article Open access CC BY 4.0

Topographic Characterization and Vegetation Distribution in Ganderbal Region of North-western Himalayas Using SRTM DEM and Sentinel-2A Data

Basira Mehraj, Akhlaq Amin Wani, M. A. Islam, Shah Murtaza, Aasif Ali Gatoo, Arshy Hussain, Tahera Arjumand, Raziya Banoo, Jamsheed Bin Jabbar

International Journal of Environment and Climate Change · pp. 1–14 · Published 15 Jul 2026

10.9734/ijecc/2026/v16i85558

Abstract

Understanding the influence of topography on vegetation distribution and land use/land cover (LULC) is essential for the sustainable management of fragile Himalayan landscapes, where difficult terrain often limits detailed field investigations. This study was conducted in Ganderbal district, central Jammu and Kashmir, India, during 2020–2023 to characterise the topography, assess vegetation distribution, and map LULC using Sentinel-2A imagery, SRTM DEM data, and GIS techniques. Sentinel-2A imagery from 2020 was used to derive the Normalised Difference Vegetation Index (NDVI) and prepare the LULC map, while SRTM-derived digital elevation data were used to generate topographic layers. The LULC classification comprised six categories: tree-based vegetation, open lands, settlements, water bodies, snow, and rocky wasteland. The study revealed a highly diverse mountainous landscape, with slopes ranging from nearly level to very steep and considerable variation in aspect. NDVI values ranged from −1 to +0.83, indicating marked spatial differences in vegetation density across the district. Tree-based vegetation was the dominant land-cover class, occupying 49.60% of the total area, followed by open lands (26.59%). The LULC classification achieved an overall accuracy of 88.18%, with a Kappa coefficient of 0.845. Vegetation patterns closely reflected the topographic setting, with lower elevations largely occupied by agriculture, horticulture, and settlements, while higher elevations were characterised by temperate forests, alpine meadows, rocky terrain, and seasonal snow. Variations in slope and aspect further influenced vegetation distribution by modifying solar radiation, soil moisture, and local microclimatic conditions. The findings provide useful spatial information for land-use planning, forest and watershed management, biodiversity conservation, and sustainable natural resource management in the Kashmir Himalayas.

Topography vegetation distribution land use/land cover normalised difference vegetation index Sentinel-2A SRTM DEM geographic information system remote sensing

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