AUTOMATIC DETECTION OF SLOPE FAILURE REGIONS USING SEMANTIC SEGMENTATION

Abstract

In Japan, slope failures associated with earthquakes and heavy rainfall occur frequently. In order to assess the damage, several organizations, including the Geographical Survey Institute (GSI), have drawn maps showing the slope failure area from aerial photographs. However, in the mapping process, the workers are manually reading the slope failure area visually, which requires a lot of labor and costs. In addition, it is difficult to map the area manually, which hinders the rapid assessment of the damage. To solve this problem, research is being conducted to detect slope failure area using artificial intelligence technology such as deep learning. In this study, we propose a method for automatic detection of slope failure regions using semantic segmentation by deep learning. The establishment of this method is aimed at efficient detection of slope failure areas and rapid assessment of damage.