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<p>Mining activities have long been a part of human civilization, but they also have significant environmental impacts, including land degradation, pollution, climate change, and biodiversity loss. This article examines the impact of open-cast mining on the Paschim Bardhaman district of West Bengal, which has a rich history of coal fields and heavy industrial towns. The study uses Support Vector Machine (SVM) and Landsat imagery to classify LULC into seven classes: water body, forest cover, sparse vegetation, agriculture, built-up, bare land, and mining area. The accuracy of LULC was validated, showing significant increases in agricultural land, built-up areas, sparse vegetation, and mining areas over a 31-year period. The study also focused on the time series analysis of rainfall (1992–2022), finding that mining activities have increased, leading to a negative trend in rainfall. The study also examined air pollution, with the aerosol optical depth (AOD) indicating a positive trend over time. The future rainfall pattern and AOD concentration in the air have been predicted by applying the popular model of autoregressive integrated moving average (ARIMA). The forecasted average rainfall for the next 10 years was found to be decreasing in nature, and the forecasted average AOD was 0.644, 0.631, and 0.632 for the years 2023, 2024, and 2025, respectively. The analysis of changing LULC, rainfall patterns, and AOD concentration in the air highlights the environmental factors impacted by mining and heavy industrialization in the study area.</p>

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Temporal Analysis of Land Use Change, Rainfall Variability and Aerosol Optical Depth in Coal Mining Areas of West Bengal, India Using Multivariate Techniques

  • 期刊论文

  • 发表日期：

    2025年11月25日

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  • David Durjoy Lal Soren,
  • Brototi Biswas,
  • Kailash Chandra Roy

摘要

Mining activities have long been a part of human civilization, but they also have significant environmental impacts, including land degradation, pollution, climate change, and biodiversity loss. This article examines the impact of open-cast mining on the Paschim Bardhaman district of West Bengal, which has a rich history of coal fields and heavy industrial towns. The study uses Support Vector Machine (SVM) and Landsat imagery to classify LULC into seven classes: water body, forest cover, sparse vegetation, agriculture, built-up, bare land, and mining area. The accuracy of LULC was validated, showing significant increases in agricultural land, built-up areas, sparse vegetation, and mining areas over a 31-year period. The study also focused on the time series analysis of rainfall (1992–2022), finding that mining activities have increased, leading to a negative trend in rainfall. The study also examined air pollution, with the aerosol optical depth (AOD) indicating a positive trend over time. The future rainfall pattern and AOD concentration in the air have been predicted by applying the popular model of autoregressive integrated moving average (ARIMA). The forecasted average rainfall for the next 10 years was found to be decreasing in nature, and the forecasted average AOD was 0.644, 0.631, and 0.632 for the years 2023, 2024, and 2025, respectively. The analysis of changing LULC, rainfall patterns, and AOD concentration in the air highlights the environmental factors impacted by mining and heavy industrialization in the study area.