This study reveals that extensive coal mining in Central India has led to significant deforestation, water loss, and agricultural decline, with land degradation worsening over three decades, highlighting the urgent need for sustainable land management and restoration to achieve Zero Net Land Degradation in mined areas.
Authors
Tarun Kumar Thakur, Department of Environmental Science, Indira Gandhi National Tribal University, Amarkantak, Madhya Pradesh, India
S. L. Swamy, College of Agriculture, Indira Gandhi Agricultural University, Bilaspur, Chhattisgarh, India
Joystu Dutta, Department of Environmental Science, Sant Gahira Guru Vishwavidyalaya, Ambikapur, Chhattisgarh, India
Anita Thakur, Krishi Vigyan Kendra, Indira Gandhi National Tribal University, Amarkantak, Madhya Pradesh, India
Alka Mishra, Guru Ghasidas University, Bilaspur, Chhattisgarh, India
Prakash Kumar Sarangi, College of Agriculture, Central Agricultural University, Imphal, Manipur, India
Amit Kumar, School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing, China
Bader O. Almutairi, Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
Rupesh Kumar, Associate Professor, Jindal Global Business School (JGBS), O. P. Jindal Global University, Sonipat, Haryana, India
Summary
Anthropogenic disturbances resulting from extensive mining activities in tropical regions pose significant threats to native land use, leading to deforestation, biodiversity loss, climate change impacts, environmental degradation, health risks, landscape fragmentation, compromised ecological security, and societal wellbeing. Monitoring Land Use and Land Cover Change (LULCC) becomes imperative for evaluating the extent and nature of land degradation in mined areas.
Methods
This study examined and compared land cover change patterns across three coalmined sites: Sohagpur (Site-I), Jamuna & Kotma (Site-II), Bishrampur (Site-III) in Central India over 3 decades using Landsat satellite imagery from 1994, 2007, and 2022. The Maximum Likelihood (ML) algorithm, within a supervised classification framework, was applied to discern mining impacts on decadal land use shifts.
Results and discussion
The analysis revealed that 7.32%–17.61% of forest cover, 5.0%–10% of water bodies, and 3%–5% of agricultural lands were lost due to mining activities, with Site three and Site two experiencing greater losses compared to Site 1. Overall, native land cover diminished by 35% between 1994 and 2022. Indices including Soil Index, Climate Index, Terrain Index, Land Utilization Index, and Vegetation Index were derived to assess land degradation patterns. These indices were integrated using a weighted index model in ArcGIS to generate the Land Degradation Vulnerability Index (LDVI). Vulnerability notably escalated with mining expansion, particularly pronounced at Site 3 (Bishrampur) and lower at Site 1 (Sohagpur). The “extremely vulnerable” class encompassed a substantial area (25%–40%), while the “low vulnerable” class was less than 5% across all sites. This study’s comprehensive analysis aids policymakers, planners, and managers in prioritizing targeted interventions and implementing sustainable land management 175 practices for ecorestoration, aligning with the goal of Zero Net Land Degradation 176 (ZNLD) in coal-mined landscapes.
Published in: Frontiers in Environmental Science
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