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Evaluation of Reclamation Soil Quality in Coal Mining Subsidence Area Based on CA-CDA-PCA-MF

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  • Shiliang Liu

    (School of Civil Engineering, Shandong University, Jinan 250061, China)

  • Yusheng Zheng

    (School of Civil Engineering, Shandong University, Jinan 250061, China)

  • Xueqiang Lv

    (Shandong Ding’an Testing Co., Ltd., Jinan 250032, China)

  • Bochao An

    (Shandong Ding’an Testing Co., Ltd., Jinan 250032, China)

  • Zhichao Huo

    (Shandong Ding’an Testing Co., Ltd., Jinan 250032, China)

  • Fangru Guo

    (Shandong Ding’an Testing Co., Ltd., Jinan 250032, China)

  • Chen Chao

    (School of Civil Engineering, Shandong University, Jinan 250061, China)

  • Deqiang Mao

    (School of Civil Engineering, Shandong University, Jinan 250061, China)

Abstract

Soil reclamation is essential for restoring the ecological environment in coal mining subsidence areas, with reclaimed soil quality serving as a key indicator of success. Traditional evaluation methods often rely on subjective judgment, leading to potential biases. This study proposes an approach combining cluster analysis (CA), correlation degree analysis (CDA), principal component analysis (PCA), and membership function (MF) to evaluate soil reclamation quality in the Ezhuang subsidence area, Shandong Province, China. A minimum dataset (MDS) was established, including seven indicators: exchangeable magnesium, total nitrogen, available copper, available manganese, zinc, free iron, and available silicon. Soil quality indices (SQIs) were calculated using membership functions, revealing moderate soil quality across the reclamation area, with significant spatial variations. The northeastern section exhibited relatively good soil quality, while the northwestern and southeastern sections were poorer. Key factors influencing soil quality included variations in organic matter, exchangeable magnesium, and available copper. The accuracy of the CA-CDA-PCA-MF method was validated, with a coefficient of determination (R 2 ) of 0.877 and a coefficient of deviation (CV) of 0.053, demonstrating its reliability. This method provides a robust tool for evaluating and improving soil restoration in mining areas, with potential applications in similar reclamation projects.

Suggested Citation

  • Shiliang Liu & Yusheng Zheng & Xueqiang Lv & Bochao An & Zhichao Huo & Fangru Guo & Chen Chao & Deqiang Mao, 2025. "Evaluation of Reclamation Soil Quality in Coal Mining Subsidence Area Based on CA-CDA-PCA-MF," Sustainability, MDPI, vol. 17(6), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2561-:d:1612361
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    References listed on IDEAS

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    1. Johnstone, Iain M. & Lu, Arthur Yu, 2009. "On Consistency and Sparsity for Principal Components Analysis in High Dimensions," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 682-693.
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