Assessment of Slope Instability in Post-Wildfire Areas Using UAV-derived DTM and QGIS Park J. W.1, Koo S1., Jung Y. H.2 and Kim S. S.3*
1 Researcher, National Disaster Management Research Institute, Republic of Korea
2 Senior Researcher, National Disaster Management Research Institute, Republic of Korea
3 Senior Research Officer, National Disaster Management Research Institute, Republic of Korea
*sskim73[at]korea.kr (*Corresponding author^s email only)
Abstract
Wildfires significantly increase slope instability by inducing vegetation loss, topsoil erosion, and the formation of hydrophobic layers. When combined with rainfall, these changes can lead to large-scale mass movement phenomena such as landslides and debris flows within a short period. However, conventional slope instability assessments based on satellite imagery or field observations often lack the spatial resolution and accuracy required for detailed analysis. In contrast, UAV-based photogrammetry enables the acquisition of high-spatial-resolution imagery and point cloud data at centimeter-level precision, allowing for fine-scale analysis of ground cover under the burned canopy. In this study, UAV photogrammetry was acquired using a state-of-the-art DJI Matrice 350 RTK drone equipped with a Zenmuse P1 optical camera. A Digital Elevation Model (DEM) was generated through DJI Terra software, and terrain analysis was conducted using QGIS. The analysis included slope mapping and distance evaluation between slopes and residential structures. Considering the lack of vegetation in the post-fire environment, the results demonstrate that UAV-based photogrammetry can serve as an effective tool for high-spatial-resolution slope instability assessment. This approach presents a practical and scalable methodology that can contribute valuable data for post-wildfire disaster response and recovery planning.
