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Article

Evaluation of Mine Land Ecological Resilience: Application of the Vague Sets Model Under the Nature-Based Solutions Framework

1
Jiangxi Provincial Key Laboratory of Safe and Efficient Mining of Rare Metal Resources, Jiangxi University of Science and Technology, Ganzhou 341000, China
2
School of Safety Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
3
Yichun Lithium New Energy Industry Research Institute, Jiangxi University of Science and Technology, Yichun 336000, China
*
Author to whom correspondence should be addressed.
Sustainability 2026, 18(1), 164; https://doi.org/10.3390/su18010164
Submission received: 20 November 2025 / Revised: 17 December 2025 / Accepted: 22 December 2025 / Published: 23 December 2025
(This article belongs to the Special Issue Sustainable Solutions for Land Reclamation and Post-mining Land Uses)

Abstract

To achieve a scientific evaluation of land ecological resilience in mining areas and promote the green transformation and sustainable development of the mining industry, this study is based on the core concept of Nature-based Solutions (NbS), coupling the “Driving force–Pressure–State–Impact–Response” (DPSIR) framework, and constructs an evaluation system for mine land ecological resilience (MLER) focusing on sustainability. This system covers multiple aspects, including natural ecology, socio-economics, and policy management, comprising 21 secondary indicators that comprehensively respond to NbS’ fundamental principles of “nature-guided, multi-party collaboration, and long-term adaptation.” In terms of evaluation methodology, this study proposes a combined weighting model that integrates AHP-CRITIC game theory with Vague sets. First, subjective expert experience and objective data variance are balanced through combined weighting. Based on game theory, the optimal combination coefficients were determined (α1 = 0.624, α2 = 0.376) to reconcile subjective and objective preferences. Subsequently, the three-dimensional interval structure of Vague sets is utilized to effectively accommodate fuzzy information and data gaps. By characterizing the restoration process through interval membership, the model enhances the representational capacity of the evaluation results regarding complex ecological information. Empirical research conducted in the mining areas of Gan Xian, Xing Guo, Yu Du, and Xun Wu in Jiangxi Province effectively identified differences in resilience levels: the resilience of the Xing Guo mining area was classified as I, Gan Xian and Yu Du as II, and Xun Wu as IV. These results are fundamentally consistent with the AHP-Fuzzy Comprehensive Evaluation method, verifying the robustness and reliability of the model. The NbS-guided evaluation system and model constructed in this study provide scientific tools for identifying differences in the sustainability of MLER and key constraints, promoting the transformation of restoration models from “engineering-driven” to “nature-driven, long-term adaptation” in the context of NbS in China.
Keywords: sustainability of mine land; vague sets; NbS; game theory sustainability of mine land; vague sets; NbS; game theory

Share and Cite

MDPI and ACS Style

Feng, L.; Xie, J.; Ke, Y. Evaluation of Mine Land Ecological Resilience: Application of the Vague Sets Model Under the Nature-Based Solutions Framework. Sustainability 2026, 18, 164. https://doi.org/10.3390/su18010164

AMA Style

Feng L, Xie J, Ke Y. Evaluation of Mine Land Ecological Resilience: Application of the Vague Sets Model Under the Nature-Based Solutions Framework. Sustainability. 2026; 18(1):164. https://doi.org/10.3390/su18010164

Chicago/Turabian Style

Feng, Lu, Jing Xie, and Yuxian Ke. 2026. "Evaluation of Mine Land Ecological Resilience: Application of the Vague Sets Model Under the Nature-Based Solutions Framework" Sustainability 18, no. 1: 164. https://doi.org/10.3390/su18010164

APA Style

Feng, L., Xie, J., & Ke, Y. (2026). Evaluation of Mine Land Ecological Resilience: Application of the Vague Sets Model Under the Nature-Based Solutions Framework. Sustainability, 18(1), 164. https://doi.org/10.3390/su18010164

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