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DOI: Comparative Analysis of Ecological Restoration Methods Applied to Rehabilitate Mining Sites: A Case Study of the Fushun and Pingshuo Mining Sites in China Using Remote Sensing Techniques Between 2000 and 2024
Gill Ammara , School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China Abaid Ur Rehman Nasir , Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, 38000 Pakistan Hongwei Zhang , School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454000, China Changhua LIU , School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China Xiaojun NIE , School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaAbstract
This study presents a comparative analysis of ecological restoration methods employed to rehabilitate mining sites, focusing on the Fushun and Pingshuo mining areas in China. Given the significant environmental degradation which has resulted from the mining activities. Effective restoration strategies are essential for enhancing biodiversity and ecological integrity. This research evaluates changes in vegetation cover and environmental health at both sites while employing metrics such as the Normalized Difference Vegetation Index (NDVI) and land cover classification utilizing remote sensing techniques. This study addresses three primary objectives which are: assessing vegetation recovery post-restoration, analyzing soil and water quality improvements, and comparing the effectiveness of various restoration methods. Preliminary findings indicate that while both sites have achieved notable vegetation recovery, differences in restoration techniques, regulatory frameworks, and environmental conditions influence outcomes. This research takes into account the important role of remote sensing in monitoring restoration success and informs best practices for future ecological restoration initiatives in mining-affected regions.
Keywords
Remote Sensing, Ecological Restoration, NDVI
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Copyright (c) 2025 Gill Ammara, Abaid Ur Rehman Nasir, Hongwei Zhang, Changhua LIU, Xiaojun NIE
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