{
  "abstract": "Mining disturbs regional environments and triggers geological hazards. Existing studies rely on conventional topographic and geological factors, neglecting quantitative mining disturbance analysis and its evolutionary impact. Disentangling mining's net effect from natural evolution via counterfactual scenarios and revealing its spatial differentiation and distance-decay on susceptibility is the key question. Taking Fuyuan County, Yunnan, as study area, this paper proposes a two-stage framework quantifying mining disturbance impacts on susceptibility through comparative modelling between hypothetical stable and actual growth periods. CA–Markov (1992–2001) projected 2002–2011 counterfactuals for four disturbance factors (FVC, land use, road density, RSEI) absent intensified mining. RF with topographic/geological factors modeled both-period susceptibility. TS-EMD extracted net mining disturbance across both layers, quantifying spatiotemporal patterns. Results: (1) Extremely high susceptibility zones expanded by 368.45 km 2 (an 11.4-percentage-point increase) during the actual growth period, while all other susceptibility zones declined. (2) Fractional Vegetation Cover (FVC), land use, road density and Remote Sensing Ecological Index (RSEI) all greatly affect hazard susceptibility, with RSEI showing the strongest impact. (3) Mining disturbance has distinct spatial heterogeneity and a distance attenuation effect. This framework supports mine disaster prevention, ecological restoration and sustainable mining.",
  "abstract_shown": true,
  "affiliations": [
    "Faculty of Geography, Yunnan Normal University, Kunming, 650500, China",
    "Yunnan Institute of Geology and Mineral Surveying and Mapping Co., Ltd, Kunming, 650051, China; Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming, 650051, China; Corresponding authors at: Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming 650051, China.",
    "Yunnan Institute of Geology and Mineral Surveying and Mapping Co., Ltd, Kunming, 650051, China; Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming, 650051, China",
    "Faculty of Geography, Yunnan Normal University, Kunming, 650500, China; Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming, 650051, China",
    "Faculty of Geography, Yunnan Normal University, Kunming, 650500, China; Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming, 650051, China; Corresponding authors at: Yunnan Key Laboratory of Intelligent Monitoring and Spatiotemporal Big Data Governance of Natural Resources, Kunming 650051, China."
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jufang Chen"
    },
    {
      "affs": [
        1
      ],
      "name": "Yamei Feng"
    },
    {
      "affs": [
        2
      ],
      "name": "Shaowen Cao"
    },
    {
      "affs": [
        2
      ],
      "name": "Wenbin Xie"
    },
    {
      "affs": [
        3
      ],
      "name": "Jia Li"
    },
    {
      "affs": [
        4
      ],
      "name": "Ping Duan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3hfctnbhh4jnm.bib",
  "cited_by": 0,
  "doi": "10.1016/j.pdisas.2026.100759",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S2590061726002450",
  "id": "3hfctnbhh4jnm",
  "issns": [
    "2590-0617"
  ],
  "landing_url": "https://doi.org/10.1016/j.pdisas.2026.100759",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "GE1-350"
    ],
    [
      "lcc",
      "H1-99"
    ],
    [
      "openalex",
      "2205|Geotechnical and Mining Engineering"
    ]
  ],
  "openalex": "W7221746572",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/3hfctnbhh4jnm.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:43:44Z",
      "native_id": "c3e92c162b0f498c84684492bc1ffea8",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.pdisas.2026.100759"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "lcc:GE1-350",
      "subfield": "environmental-science"
    }
  ],
  "title": "Two-stage assessment of regional geological hazard susceptibility under mining disturbance",
  "title_text": "Two-stage assessment of regional geological hazard susceptibility under mining disturbance",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:43:44Z",
  "url": "https://research.draconitic.com/paper/3hfctnbhh4jnm",
  "venue": "Progress in Disaster Science",
  "versions": []
}