Geological Safety Evaluation of Urban Areas in Northeastern Chongqing Using a Multi-Source Logistic Regression Model
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 R2 ≥ 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.
Authors
- Tong Jiang (ORCID: https://orcid.org/0000-0002-9138-3398)
- D.Q. Li
- Shaokai Wang (ORCID: https://orcid.org/0009-0003-2741-7914)
- Luqi Wang
- Yahui Liang
- Zhihao Chen
- Yanchang Jia
- Pengfei Liu
Institutions
- Chongqing University (CN)
- North China University of Water Resources and Electric Power (CN)
- Chongqing Bureau of Geology and Minerals Exploration (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2026-01-02
- DOI
- https://doi.org/10.3390/su18010450
- Primary Topic
- Landslides and related hazards
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- North China University of Water Resources and Electric Power
- National Natural Science Foundation of China
- National Key Research and Development Program of China