AHP-EWM Based Model Selection System for Subsidence Area Research

• Published in: Sustainability 2023-04, Vol.15 (9), p.7135
• Main Authors: Liang, Ming, Yang, Gen, Zhu, Xiaojun, Cheng, Hua, Zheng, Liugen, Liu, Hui, Dong, Xianglin, Zhang, Yanhai
• Format: Article
• Language: English
• Subjects: Analysis; Coal; Coal industry; Coal mining; Ecological effects; Entropy (statistics); Environmental impact; Geographical locations; International standards; Land reclamation; Land use; Mineral industry; Mines; Mining industry; Quantitative analysis; Remote sensing; Software packages; Subsidence; Sustainability; Vegetation; Weighting methods
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su15097135

Coal mining can create a variety of environmental, ecological, and land-use problems. Subsidence areas resulting from coal mining are a common and particularly difficult problem to manage. Despite much discussion in the academic literature as well as among local and international stakeholders, there is neither a uniform standard nor a universally accepted approach for selecting an appropriate governance model for a subsidence area. In particular, the lack of quantitative evaluation methods and excessive subjectivity represent key obstacles to the effective selection of governance models for subsidence areas. This paper proposes a selection framework for a coal mining subsidence governance model that integrates the analytic hierarchy process (AHP) and entropy weight method (EWM). The model comprehensively considers the settlement characteristics of the subsidence area, its geographic location, the water index, as well as the vegetation index. These variables are used as indicators to develop an evaluation framework upon which different subsidence zones can be quantitatively analyzed. The selection framework is demonstrated using examples from three subsidence areas in the Huainan and Huaibei mining areas in China, for which relevant data were collected and processed with the help of field surveys, remote sensing images, and subsidence prediction software. Applying the novel selection framework, the most suitable governance model for each subsidence area was obtained and determined to be consistent with the recommendations of an academic panel composed of multiple experts. The novel selection framework has high efficacy and potential to overcome the problem of subjectivity in the selection of governance models for coal mining subsidence areas. It is also envisaged that future incorporation of the selection framework into a user-friendly software package will significantly improve the efficiency with which suitable governance models for coal mining subsidence areas are selected.