Abstract. Due to abnormal weather caused by climate change in recently years, natural disaster damages caused by local torrential rains have been increased over the world. Particularly, Korea is very vulnerable to landslide disasters because more than 63% of the country is mountainous and it suffers from unpredictable localized heavy rainfall during monsoon season every year. This paper presents experimental results for risk assessment of steep slope using drone mapping and terrestrial LiDAR survey. First, we acquired the aerial imagery of steep slope site by small UAV and conducted a drone mapping process with the Pix4D software. For collecting the more detailed geological data and analysing quantitatively damage of steep slopes (crack length, bedrock weathering area, etc.), we scanned steep slope area using terrestrial LiDAR system. Finally, we evaluated the applicability of public safety for outputs of UAV photogrammetry and 3D point clouds derived from terrestrial LiDAR data to analyse and assess the risk of steep slope.
Abstract. Recently, UAVs are being used in various fields such as photography, precision agriculture, remote monitoring, surveying, mapping, and disaster management. In particular, UAVs can acquire real-time data and access hard-to-reach areas, which is advantageous for rapid spatial information generation. Spatial information can be generated by mounting a camera on the UAV and performing the geocoding process of image data using the location/location information acquired from the GPS/INS sensor. The use of multiple GCPs during the geocoding process can increase the image position accuracy. However, since a lot of time is consumed for surveying, it is disadvantageous to be used in disaster fields that require urgent data generation. Therefore, in this study, fast geocoding process of UAV image using the minimum GCP is proposed. The results obtained through this process can be used as basic data for on-site monitoring and decision-making in disasters and emergencies.
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