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Analysis of Eco-Environmental Quality and Driving Forces in Opencast Coal Mining Area Based on GWANN Model: A Case Study in Shengli Coalfield, China

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  • Ming Chang

    (China Energy Digital Intelligence Technology Development (Beijing) Co., Ltd., Beijing 100011, China
    Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China)

  • Shuying Meng

    (China Energy Digital Intelligence Technology Development (Beijing) Co., Ltd., Beijing 100011, China)

  • Zifan Zhang

    (Natural Resources Comprehensive Survey Command Center, China Geological Survey, Beijing 100055, China)

  • Ruiguo Wang

    (China Energy Digital Intelligence Technology Development (Beijing) Co., Ltd., Beijing 100011, China)

  • Chao Yin

    (China Institute of Nuclear Industry Strategy (CINIS), Beijing 100048, China)

  • Yuxia Zhao

    (Department of Architecture, University of Florence, 50121 Florence, Italy)

  • Yi Zhou

    (Natural Resources Comprehensive Survey Command Center, China Geological Survey, Beijing 100055, China)

Abstract

Opencast coal mine production and construction activities have a certain impact on the ecological environment, while the development and utilization of large coal bases distributed in semi-arid steppe regions may have a more direct and significant impact on the eco-environment. Therefore, in-depth studies of the ecological impacts of human activities and natural environmental elements in opencast coal mines in typical semi-arid steppe regions and analyses of their driving forces are of great significance for protecting and restoring regional fragile steppe ecosystems. In this paper, the mining area southwest of the Shengli coalfield, a typical ore concentration area in eastern Inner Mongolia, was selected as the research object. Its remote sensing ecological index (RSEI) was calculated using the Google Earth Engine (GEE) platform to analyze the eco-environmental quality in the mining area and its surrounding 2 km from 2005 to 2021. The geographically weighted artificial neural network model (GWANN) was combined with the actual situation of mining activity and ecological restoration to discuss the driving factors of eco-environmental quality change in the study area. The results showed that: (1) the proportion of the study area with excellent and good eco-environmental quality increased from 20.96% to 23.93% from 2005 to 2021, and the proportions of areas with other quality grades fluctuated strongly. (2) The change in eco-environmental quality in the interior of the mining area was closely related to the reclamation of dump sites and migration of the mining area. (3) The maximum contribution rate of the mining activity factor to the external eco-environmental quality of the mining area reached 43.33%, with an annual average contribution rate of 34.48%; as the distance from the mining area increased, its contribution gradually decreased. This quantitative analysis of the driving forces of RSEI change in the mining area will complement future work in ecological evaluations of mining areas while also improving the practicality of ecological evaluation at the mining scale, thereby further helping the ecological management of mining areas.

Suggested Citation

  • Ming Chang & Shuying Meng & Zifan Zhang & Ruiguo Wang & Chao Yin & Yuxia Zhao & Yi Zhou, 2023. "Analysis of Eco-Environmental Quality and Driving Forces in Opencast Coal Mining Area Based on GWANN Model: A Case Study in Shengli Coalfield, China," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10656-:d:1187993
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    References listed on IDEAS

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