Utilizaing Drone Mapping Technology for Hazard Assessment of Steep Slopes Jung Y.H.(a), Lim E.T.(b), Koo S.(c), Park J.W.(c), Suk J.W.(d), and Kim S.S.(e*)
a) Senior Researcher, Disaster Scientific Investigation Div., National Disaster Management Research Institute, Rep. of Korea
b) Senior Researcher, Disaster Resilience Research Center., National Disaster Management Research Institute, Rep. of Korea
c) Researcher, Disaster Scientific Investigation Div., National Disaster Management Research Institute, Rep. of Korea
d) Research Officer, Safety Research Div., National Disaster Management Research Institute, Rep. of Korea
e) Senior Research Officer, Disaster Scientific Investigation Div., National Disaster Management Research Institute, Rep. of Korea
* sskim73[at]korea.kr
Abstract
During the thawing season, when frozen ground begins to melt, the risk of slope-related disasters such as rockfalls, landslides, and road subsidence increases significantly. Coastal steep slopes, particularly cliff-type terrains adjacent to seaside roads, are prone to frequent rockfalls due to continuous wave-induced erosion and weathering. In the Republic of Korea, annual inspections are conducted under the ^Act on the Prevention of Disasters on Steep Slopes,^ led by expert teams that assess slope stability. However, conventional ground-based surveys often face limitations in visibility and accessibility due to vegetation and slope height. To overcome these challenges, this study explores the use of drone mapping technology as a complementary method for hazard assessment.
The study focuses on Hyeonpo-ri District in Ulleung-gun, where a massive rockfall event involving approximately 100 tons of debris occurred in March 2025. Drones were deployed to capture high-resolution imagery of inaccessible upper slopes. High-resolution images were captured from multiple angles, and processed into orthomosaics, 3D models, and point clouds. These products enabled detailed identification of rockfall zones, slope geometry, and collapse features, surpassing the capabilities of traditional visual inspections. The estimated collapsed area was also quantified using point cloud analysis. As a result, the site was assigned a hazard risk score of 69 (Grade D).
This study demonstrates the applicability of drone mapping technology for evaluating slope hazard potential in the Hyeonpo-ri area, where a significant rockfall had occurred. By overcoming the accessibility constraints of conventional ground-based surveys, drone-based methods provide high-resolution spatial data that enable more accurate and quantitative risk assessments. The approach holds promise for future disaster prevention and hazard analysis in similar topographic settings.
Keywords: UAV, Disaster risk assessment, Point cloud, 3D modeling, Geospatial analysis
