Road Blockage Estimation Using Remote Sensing Terrain Data from Disaster Areas

Abstract

Road blockages caused by landslides and debris flows obstruct emergency vehicles and delay rescue operations. Rapid identification of blocked roads is therefore essential for effective disaster response. This paper proposes a road blockage estimation method using terrain data obtained by remote sensing and interpolation method based on roadside regions. First, vegetation is removed from orthoimages to reduce the influence of trees, and terrain changes are extracted by calculating the difference between pre- and post-disaster Digital Elevation Model (DEM) generated from 3D point cloud data. Candidate sediment areas are then obtained by combining the vegetation mask with the DEM difference. To compensate for areas where sediment is difficult to detect directly, sediment information detected in roadside regions is interpolated into the road area, enabling more robust road blockage detection. Finally, blockage conditions are determined for each road segment and visualized on a road network. The proposed method was evaluated using post-disaster sediment maps and visually interpreted orthoimages. Experimental results demonstrate that the proposed roadside interpolation improves the detection of sediment-related road blockages and confirms the effectiveness of integrating terrain data with road information.