Evaluation of geological hazard susceptibility based on the multi-kernel density information method
Abstract The increasing occurrence of geological hazards along roadway infrastructures presents a significant concern. Evaluating geological hazard susceptibility along roads is a critical aspect of geological disaster emergency response and rescue efforts. Accurate evaluation outcomes are essential...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-91713-6 |
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| Summary: | Abstract The increasing occurrence of geological hazards along roadway infrastructures presents a significant concern. Evaluating geological hazard susceptibility along roads is a critical aspect of geological disaster emergency response and rescue efforts. Accurate evaluation outcomes are essential as they play a crucial role in mitigating potential financial losses. However, previous studies on geological hazard susceptibility treated all samples as independent entities, overlooking their spatial interactions. This study introduces a novel geological hazard susceptibility assessment model termed the multi-kernel density information (MKDI) method. The MKDI method integrates information value with kernel density estimation, effectively capturing the spatial dependencies among samples. Furthermore, distinct bandwidths are prescribed for various scales of disasters to facilitate multi-kernel density estimation for geological hazards. The integration of the information method enables the development of a comprehensive geological hazard susceptibility map, capturing the spatial complexities of geological hazard distribution. To validate the effectiveness of the proposed method, the study area selected for investigation was the G219 National Highway within Zayu County. Various factors were considered for geological hazard susceptibility mapping, including slope, aspect, profile and plan curvature, river and road linear densities, peak ground acceleration, seismic response spectrum characteristics, lithology, elevation, rainfall, and landform. The results show that the MKDI model outperformed previous methods, achieving an AUC value of 0.99. The derived susceptibility map is expected to offer a scientific basis for urban planning, construction, and geological hazard risk management in the study area. |
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| ISSN: | 2045-2322 |