| dc.description.abstract | The losses caused by earthquakes are not only directly attributable to the seismic shaking but also to the significant contribution of landslides triggered by the seismic activity. Therefore, it is crucial to quickly and accurately determine the locations where landslides may have occurred after an earthquake, in order to develop effective strategies for post-disaster rescue and emergency response.
The objective of this study is to generate semi-automatically near-real-time susceptibility maps for landslides, aiming to minimize manual data processing time. In this study, logistic regression is used to calculate the susceptibility. The model selected the following factors: slope, slope roughness, terrain roughness, total curvature, slope height, Arias Intensity, aspect, and lithology. The data is partitioned based on the Arias Intensity, and two models are designed using two different training data sampling methods to calculate the susceptibility values for different intensities. The study also evaluates the influence of inherent factors on susceptibility values under different intensities.
This study developed a semi-automated Python program to calculate susceptibility. Through testing, it was found that the program can establish a landslide susceptibility model within one minute and generate a susceptibility map in approximately 15 minutes. In the future, the aim is to integrate techniques for aftershock prediction. When a main shock occurs, the established landslide susceptibility model can be used to create an initial version of the susceptibility map. Then, with the automatic interpretation of remote sensing data for landslide inventories and seismic signals from strong motion stations, a new model can be constructed using the landslide catalog induced by the main shock. By combining this with aftershock prediction techniques and the spatial distribution of shaking intensity caused by aftershocks, it will be possible to predict the distribution of landslides that may occur as a result of aftershocks. This information can serve as an important reference material for rescue or emergency response after a main shock. | en_US |