Land Degradation Vulnerability Associated With Coal Mining Expansion in Central India: A 25‐Year Remote Sensing, GIS, and Multi‐Criteria Assessment

Thakur, Tarun Kumar, Patel, Digvesh Kumar, Eripogu, Kiran Kumar, Maharathi, Payal, Thakur, Anita, Kumar, Amit and Kumar, Rupesh ORCID: https://orcid.org/0000-0002-6590-4313 (2026) Land Degradation Vulnerability Associated With Coal Mining Expansion in Central India: A 25‐Year Remote Sensing, GIS, and Multi‐Criteria Assessment. CLEAN – Soil, Air, Water, 54 (9): e70281. John Wiley and Sons Ltd . ISSN 1863-0650 Available at: https://doi.org/10.1002/clen.70281

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Abstract

Rapid open‐cast coal mining expansion in Central India has accelerated environmental degradation across major coalfield regions of Madhya Pradesh and Chhattisgarh. Extensive land clearing has resulted in forest loss, overburden dump expansion, soil deterioration, and alterations in surface water distribution. This study evaluated land‐use and land‐cover change and land degradation vulnerability across 11 coal mining regions between 1998 and 2023. Satellite‐derived vegetation indices, moisture, built‐up, and water indices were integrated with soil analyses to assess vegetation cover and condition, surface moisture dynamics, urban expansion, hydrological landscape, and soil quality. A land degradation vulnerability index was developed through an integrated remote sensing, GIS, analytic hierarchy process, and geospatial modeling approach. Land‐use classifications achieved overall accuracies of 88.35% ( κ = 0.86) for 1998 and 92.27% ( κ = 0.91) for 2023, while vulnerability assessment validation produced an overall accuracy of 88.37% ( κ = 0.86). The results revealed substantial forest cover decline, expansion of mining and overburden dump areas, nutrient depletion, increased soil compaction, and localized changes in surface water distribution. Forest cover declined by up to 50% in several mining regions, whereas highly vulnerable zones expanded markedly, including a more than fivefold increase in Site 5. The judgment‐based AHP assigned the highest criterion weights to elevation, vegetation condition, and surface moisture, whereas the separate site‐level correlation analysis showed strong associations of LDVI with slope ( r = 0.97), aspect ( r = 0.96), and elevation ( r = 0.88). The vulnerability framework identified priority degraded areas for immediate intervention, supporting targeted reclamation and sustainable land management.

Item Type: Article
Uncontrolled Keywords: Analytic hierarchy process | Central India | Coal mining | GIS | Land degradation | Land degradation vulnerability | Land-use and land-cover change | Remote sensing
Subjects: Physical, Life and Health Sciences > Engineering and Technology
Physical, Life and Health Sciences > Environmental Science, Policy and Law
Divisions: Jindal Global Business School
Vol/Issue no. published date: September 2026
Depositing User: Mr. Syed Anas Ali
Date Deposited: 28 Sep 2026 05:01
Last Modified: 29 Sep 2026 07:13
Official URL: https://doi.org/10.1002/clen.70281
URI: https://pure.jgu.edu.in/id/eprint/12694

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