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<p>Landslides in the Eastern Ghats Mobile Belt pose an escalating threat to both human infrastructure and fragile ecosystems, yet integrated assessments that link geophysical instability with ecological vulnerability remain rare. This study advances landslide susceptibility and ecological risk assessment in the Koraput District (8,807 km2), Odisha, through an integrated multivariate framework combining Remote Sensing (RS), Geographic Information Systems (GIS), the Analytical Hierarchy Process (AHP), DAN3D debris-flow modeling, and key biophysical indicators including Normal Difference Vegetation Index (NDVI), Land Surface Temperature (LST), RUSLE-derived soil erosion, and biodiversity indices. In contrast to conventional studies that evaluate landslide hazards and ecological degradation independently, the present approach systematically examines their spatial interactions and associated environmental feedback to provide a comprehensive understanding of landscape vulnerability in the Eastern Ghats region. Key findings reveal that 86% of major landslides (2015–2024) followed 7-day rainfall &gt; 250 mm, with susceptibility concentrated along lithological contacts (charnockite–khondalite–gneiss) and slopes &gt; 25°. The AHP model (CR = 0.03) identified geology (0.113), slope (0.102), and land use (0.102) as dominant controls. Landslide Susceptibility Zonation classifies 7.25% (638 km2) as high risk, mainly in Borigumma and NE Jeypore, while 31% of the landscape suffers water erosion (RUSLE) and 60% shows only slight vegetation cover (NDVI 0.04–0.50). Critically, high-susceptibility zones overlap directly with habitats of three endangered species (Manis crassicaudata, Pterocarpus santalinus, Cyrtodactylus jeyporensis), demonstrating that geological instability exacerbates biodiversity loss. The integrated model achieved good predictive accuracy (AUC = 0.749), offering a robust decision-support tool for hazard-sensitive land-use planning and conservation in monsoon-dominated mountain ecosystems.</p>

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Integrated landslide susceptibility zonation and ecological risk assessment in Koraput District, Eastern India: a multivariate approach

  • 期刊论文

  • 发表日期：

    2026年7月14日

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  • Tanmoy Chatterjee,
  • Janmejay Sethy,
  • Pratap Kottapalli,
  • Puspita Hazra,
  • Biswajit Ghosh,
  • Amitarani Ray,
  • Duryadhan Behera,
  • Shreerup Goswami,
  • Surajit Munshi

摘要

Landslides in the Eastern Ghats Mobile Belt pose an escalating threat to both human infrastructure and fragile ecosystems, yet integrated assessments that link geophysical instability with ecological vulnerability remain rare. This study advances landslide susceptibility and ecological risk assessment in the Koraput District (8,807 km2), Odisha, through an integrated multivariate framework combining Remote Sensing (RS), Geographic Information Systems (GIS), the Analytical Hierarchy Process (AHP), DAN3D debris-flow modeling, and key biophysical indicators including Normal Difference Vegetation Index (NDVI), Land Surface Temperature (LST), RUSLE-derived soil erosion, and biodiversity indices. In contrast to conventional studies that evaluate landslide hazards and ecological degradation independently, the present approach systematically examines their spatial interactions and associated environmental feedback to provide a comprehensive understanding of landscape vulnerability in the Eastern Ghats region. Key findings reveal that 86% of major landslides (2015–2024) followed 7-day rainfall > 250 mm, with susceptibility concentrated along lithological contacts (charnockite–khondalite–gneiss) and slopes > 25°. The AHP model (CR = 0.03) identified geology (0.113), slope (0.102), and land use (0.102) as dominant controls. Landslide Susceptibility Zonation classifies 7.25% (638 km2) as high risk, mainly in Borigumma and NE Jeypore, while 31% of the landscape suffers water erosion (RUSLE) and 60% shows only slight vegetation cover (NDVI 0.04–0.50). Critically, high-susceptibility zones overlap directly with habitats of three endangered species (Manis crassicaudata, Pterocarpus santalinus, Cyrtodactylus jeyporensis), demonstrating that geological instability exacerbates biodiversity loss. The integrated model achieved good predictive accuracy (AUC = 0.749), offering a robust decision-support tool for hazard-sensitive land-use planning and conservation in monsoon-dominated mountain ecosystems.