In light of recent natural disasters in Japan, efforts are underway on expressways managed by NEXCO (Nippon Expressway Company) to acquire 3D point cloud data across the entire network, using Airborne LiDAR, to identify landslide disaster risks originating from outside the expressway area. In this study, we conducted trial verifications by performing differential analysis of data from multiple time periods, taken before disasters occurred at five locations along expressways where landslide disasters had previously occurred, to see if signs of disaster occurrence (landslide disaster risk) could be detected. As a result, topographic changes before disaster occurrence were detected in some areas. However, such changes were not always detected depending on data accuracy, data acquisition timing, and disaster occurrence patterns. Based on these findings, key points for future data acquisition were organized.
Sasaki et al. (2026) studied this question.