EGU25-2117, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-2117
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Spatial and Temporal Analysis of Landslide Susceptibility– for the Case in Taiwan
Keh-Jian Shou
Keh-Jian Shou
  • National Chung-Hsing University, College of Engineering, Dept. of Civil Engineering, Taichung, Taiwan, Province of China (kjshou@dragon.nchu.edu.tw)

Due to the impact of climate change, the increasing frequency of extreme rainfall events, with concentrated rainfalls, commonly cause landslide hazard in the mountain areas of Taiwan. However, there are uncertainties for the predicted rainfall as well as the landslide susceptibility analysis. This study employs machine learning approached, including the logistic regression method LR to analyze the landslide susceptibilities. Together with the predicted temporal rainfall, the predictive analysis of landslide susceptibility was performed in the adopted study area in Central Taiwan. The uncertainties within the rainfall prediction was firstly investigated before applied to the landslide susceptibility analysis. To assess the susceptibility of the landslides, logistic regression method LR was applied. The results of predictive analysis, with the discussions on the accuracy and uncertainties, can be applied for the landslide hazard management.

How to cite: Shou, K.-J.: Spatial and Temporal Analysis of Landslide Susceptibility– for the Case in Taiwan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2117, https://doi.org/10.5194/egusphere-egu25-2117, 2025.