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<p>Agriculture and mining play a significant role in a nation's economic development. However, extensive mining severely damages the natural environment, leading to soil erosion, increased air and water pollution, and other ecological disturbances. This study examines the impact of excessive opencast mining on the local environment in the Joda Block of Keonjhar District, Odisha. Temporal Landsat satellite imagery from 1990 and 2020 was used, and the images were classified using the Maximum Likelihood Classifier (MLC) algorithm. The classified images were evaluated for accuracy. Once satisfactory overall accuracy and a reliable Kappa coefficient were achieved, the area covered by each land use/land cover (LULC) category was calculated. The classification results indicate a significant decline in forest land, water bodies, and cropland, with annual decline rates of 0.56%, 0.47%, and 0.87%, respectively. Conversely, mining and built-up areas increased considerably, with annual growth rates of 3.12% and 11.51%, respectively. Land Surface Temperature (LST) for 1990 and 2020 was retrieved from Landsat satellite imagery using the mono-window algorithm, revealing an increase in mean LST from 22.19&#xa0;°C in 1990 to 23.36&#xa0;°C in 2020. Remotely sensed indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI), were derived from Landsat imagery. Their correlation with LST was assessed using Pearson’s correlation coefficient. The results show a negative correlation between LST and NDVI, a weak positive correlation with NDWI, and a strong positive correlation with NDBI. This study provides valuable insights into the adverse environmental consequences of opencast mining and serves as a guide for researchers and planners in formulating sustainable environmental management strategies.</p> Graphical abstract <p></p>

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From green to gray: a geospatial study on the environmental consequences of opencast mining in Joda, Odisha

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Krishna Manjari Jena,
  • Prasanta Kumar Patra,
  • Duryadhan Behera,
  • Shreerup Goswami

摘要

Agriculture and mining play a significant role in a nation's economic development. However, extensive mining severely damages the natural environment, leading to soil erosion, increased air and water pollution, and other ecological disturbances. This study examines the impact of excessive opencast mining on the local environment in the Joda Block of Keonjhar District, Odisha. Temporal Landsat satellite imagery from 1990 and 2020 was used, and the images were classified using the Maximum Likelihood Classifier (MLC) algorithm. The classified images were evaluated for accuracy. Once satisfactory overall accuracy and a reliable Kappa coefficient were achieved, the area covered by each land use/land cover (LULC) category was calculated. The classification results indicate a significant decline in forest land, water bodies, and cropland, with annual decline rates of 0.56%, 0.47%, and 0.87%, respectively. Conversely, mining and built-up areas increased considerably, with annual growth rates of 3.12% and 11.51%, respectively. Land Surface Temperature (LST) for 1990 and 2020 was retrieved from Landsat satellite imagery using the mono-window algorithm, revealing an increase in mean LST from 22.19 °C in 1990 to 23.36 °C in 2020. Remotely sensed indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI), were derived from Landsat imagery. Their correlation with LST was assessed using Pearson’s correlation coefficient. The results show a negative correlation between LST and NDVI, a weak positive correlation with NDWI, and a strong positive correlation with NDBI. This study provides valuable insights into the adverse environmental consequences of opencast mining and serves as a guide for researchers and planners in formulating sustainable environmental management strategies.

Graphical abstract