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Geological Safety Evaluation of Urban Areas in Northeastern Chongqing Using a Multi-Source Logistic Regression Model

Author

Listed:
  • Yanchang Jia

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Zhihao Chen

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Tong Jiang

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Yahui Liang

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Dian Li

    (School of Civil Engineering, Chongqing University, Chongqing 400045, China)

  • Pengfei Liu

    (Chongqing Monitoring Station of Geological Environment, Chongqing 401147, China)

  • Luqi Wang

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    School of Civil Engineering, Chongqing University, Chongqing 400045, China
    Chongqing Monitoring Station of Geological Environment, Chongqing 401147, China)

  • Shaokai Wang

    (School of Earth Science and Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

Abstract

This study addresses the key scientific problem of urban safety in complex, hazard-inducing geological environments by focusing on representative towns in the Three Gorges Reservoir area. Through the integrated use of field investigations, numerical simulations, and multivariate statistical analysis, we developed a comprehensive model for assessing geological safety risk in reservoir-area towns. A four-tier deep safety evaluation system was constructed for two types of hazard-inducing geological environments, and a classification scheme for shallow susceptibility was proposed. On this basis, a five-tier integrated urban geological safety risk evaluation model was established that combines deep safety level, engineering sensitivity, shallow susceptibility, and prevention difficulty. The model exhibited strong performance (pseudo R 2 ≥ 0.914, p < 0.001) and indicates that risk is predominantly moderate (Grade III), with 85.7% of the 21 representative areas in Wushan, Fengjie, and other “2 + 4” towns falling into this category. Overall, the results provide an operational tool to support disaster risk reduction, risk-informed land-use governance, and resilient infrastructure planning, thereby contributing to sustainable urban development in reservoir-side mountainous regions.

Suggested Citation

  • Yanchang Jia & Zhihao Chen & Tong Jiang & Yahui Liang & Dian Li & Pengfei Liu & Luqi Wang & Shaokai Wang, 2026. "Geological Safety Evaluation of Urban Areas in Northeastern Chongqing Using a Multi-Source Logistic Regression Model," Sustainability, MDPI, vol. 18(1), pages 1-20, January.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:1:p:450-:d:1831738
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