Abstract
The geological conditions of mines are complex and diverse, and existing restoration methods may not be sufficient to meet the requirements for all types of mine rehabilitation. A study on the optimization of ecological restoration technologies for green mines based on hesitant fuzzy TOPSIS has been proposed, offering a novel approach for selecting ecological restoration solutions for rock slopes in green mines. First, a remote 3D laser scanner is used to construct a digital terrain model (DTM) for the target mine. Then, based on characteristics such as geological lithology, slope aspect, and slope angle, the open-pit mine slopes are divided into zones. Finally, the rock mass quality of each slope zone is evaluated using eight indicators, including uniaxial saturated compressive strength, rock quality designation (RQD), structural plane condition, joint spacing, and integrity coefficient. The evaluation process specifically includes: constructing a hesitant fuzzy decision matrix based on the eight key indicators for each slope zone; objectively determining the weights of the indicators using the maximum deviation method to minimize subjectivity; calculating the weighted distance between each slope zone scheme and the defined hesitant fuzzy positive/negative ideal solutions; determining the relative closeness coefficient for each zone to classify the rock mass quality grade. Based on the grading results, the most suitable ecological restoration techniques are matched to each slope zone to achieve differentiated ecological restoration. Experimental results show that the mining slope is divided into seven zones using this approach. After ecological restoration, near-ground dust is effectively controlled. The vegetation restoration rate reaches up to 25%, whereas the rates of comparative methods are all below 15%. This indicates that the proposed method can help improve restoration efficiency and quality, promote sustainable development, better meet the requirements for efficient ecological restoration in mines, and possesses practical applicability.
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Bin Wang: Writing—Original Draft Preparation, Writing—Review and Editing, Investigation, Conceptualization, Supervision, Project administration, Formal Analysis Daoran Guo: Data Curation, Writing—Original Draft Preparation, Visualization, Writing—Review and Editing, Software, Resources Jing Sun: Conceptualization, Writing—Review and Editing, Writing—Original Draft Preparation, Data Curation, Formal Analysis Jian Guo: Writing—Review and Editing, Writing—Original Draft Preparation, Investigation, Visualization Shangrong Gao: Methodology, Formal Analysis, Writing—Review and Editing, Writing—Original Draft Preparation Wanli Lu: Writing—Review and Editing, Writing—Original Draft Preparation, Data Curation.
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Wang, B., Guo, D., Sun, J. et al. Optimization of ecological and efficient restoration technology for green mines based on hesitant fuzzy TOPSIS. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37060-6
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DOI: https://doi.org/10.1038/s41598-026-37060-6
