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<p>Resource-based regions have long been subjected to intensive mining and land-use pressures, resulting in fragile and highly sensitive ecological environments. Using Landsat data from 1992 to 2022, this study developed an improved MRSEI on the GEE platform to assess the spatiotemporal evolution of habitat quality in Lingshi, a representative coal mining region in Shanxi Province. The study integrates Theil-Sen slope, Mann-Kendall test, Hurst exponent, coefficient of variation (CV), and spatial autocorrelation models, such as Global Moran’s I and Local Indicators of Spatial Association (LISA), to examine ecological trends, system stability, spatial clustering, and volatility. Key findings include: (1) habitat quality has improved overall, with MRSEI values increasing from 0.401 to 0.442, showing phase-based variation; (2) 58.9% of the area exhibited ecological improvement, with 17.5% significantly enhanced, but 30.3% still degraded and 77.3% displayed anti-persistence, indicating potential reversal of recovery; (3) spatial clustering was significant, with high-quality zones expanding eastward and degraded zones fixed in mining-affected areas; (4) high-volatility zones, mostly within mining-affected areas, accounted for nearly 30%, indicating the weakest system stability; (5) by integrating Theil-Sen, Hurst, and CV metrics, the study identifies key management units such as zones for stable enhancement, fluctuation alert, and emergency restoration. This multidimensional framework provides theoretical guidance and decision-making support for ecological risk identification, restoration prioritization, and differentiated governance in resource-dependent areas.</p> Graphical Abstract <p></p>

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MRSEI Tailored to Mining Disturbance Reveals Unstable Habitat-quality Recovery and Rebound Risk in a Coal-Mining Region (1992-2022)

  • 期刊论文

  • 发表日期：

    2026年4月29日

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  • Yedong Chen,
  • Jiang Chang,
  • Rongbing Xu,
  • Linjie Wang

摘要

Resource-based regions have long been subjected to intensive mining and land-use pressures, resulting in fragile and highly sensitive ecological environments. Using Landsat data from 1992 to 2022, this study developed an improved MRSEI on the GEE platform to assess the spatiotemporal evolution of habitat quality in Lingshi, a representative coal mining region in Shanxi Province. The study integrates Theil-Sen slope, Mann-Kendall test, Hurst exponent, coefficient of variation (CV), and spatial autocorrelation models, such as Global Moran’s I and Local Indicators of Spatial Association (LISA), to examine ecological trends, system stability, spatial clustering, and volatility. Key findings include: (1) habitat quality has improved overall, with MRSEI values increasing from 0.401 to 0.442, showing phase-based variation; (2) 58.9% of the area exhibited ecological improvement, with 17.5% significantly enhanced, but 30.3% still degraded and 77.3% displayed anti-persistence, indicating potential reversal of recovery; (3) spatial clustering was significant, with high-quality zones expanding eastward and degraded zones fixed in mining-affected areas; (4) high-volatility zones, mostly within mining-affected areas, accounted for nearly 30%, indicating the weakest system stability; (5) by integrating Theil-Sen, Hurst, and CV metrics, the study identifies key management units such as zones for stable enhancement, fluctuation alert, and emergency restoration. This multidimensional framework provides theoretical guidance and decision-making support for ecological risk identification, restoration prioritization, and differentiated governance in resource-dependent areas.

Graphical Abstract