Research and Application of Early Identification of Geological Hazards Technology in Railway Disaster Prevention and Control: A Case Study of Southeastern Gansu, China

Peng He, Zhaocheng Guo (), Hong Chen, Pengqing Shi, Xiaolong Zhou and Genhou Wang
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Peng He: School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Zhaocheng Guo: China Aero Geophysical Survey & Remote Sensing Center for Land, Beijing 100083, China
Hong Chen: China Aero Geophysical Survey & Remote Sensing Center for Land, Beijing 100083, China
Pengqing Shi: Gansu Provincial Geological Environment Monitoring Institute, Lanzhou 730050, China
Xiaolong Zhou: Gansu Provincial Geological Environment Monitoring Institute, Lanzhou 730050, China
Genhou Wang: School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China

Sustainability, 2023, vol. 15, issue 24, 1-24

Abstract: Geological hazards significantly threaten the safety of China’s railway network. As the railway system continues to expand, particularly with the effects of accelerated climate change, approximately 70% of the newly encountered geohazards occur outside of known areas. This study proposes a novel approach that can be applied to railway systems to identify potential geohazards, analyze risk areas, and assess section vulnerability. The methodology uses integrated remote sensing technology to effectively enhance potential railway hazard identification timeliness. It combines kernel density, hotspot, and inverse distance-weighted analysis methods to enhance applicability and accuracy in the risk assessment of railway networks. Using a case study in southeastern Gansu as an example, we identified 3976 potential hazards in the study area, analyzed five areas with high concentrations of hazards, and 11 districts and counties prone to disasters that could threaten the railway network. We accurately located 16 sections and 20 significant landslide hazards on eight railway lines that pose operational risks. The effectiveness of the methodology proposed in this paper has been confirmed through field investigations of significant landslide hazards. This study can provide a scientific basis for the sustainability of the railway network and disaster risk management.

Keywords: RS; GIS; early identification of geohazards; Gansu railway network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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