The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B3-2022
30 May 2022
 | 30 May 2022


S. S. Kim, D. Y. Shin, E. T. Lim, Y. H. Jung, and S. B. Cho

Keywords: Natural Disaster, Damage Investigation, Artificial Intelligence, Drone Mapping

Abstract. This study aims to testify the applicability of UAV photogrammetry and artificial intelligence (AI) for the management of natural disaster. Recently artificial intelligence is considered as an emerging tool for recognizing disaster events from aerial imagery of drones. In this paper, we present firstly the approach related to use of AI techniques for disaster detecting and identification. Secondly, we suggest small easy-to-use UAV-based investigation procedure for natural disaster damaged area in the phase of disaster recovery in Korea. Finally, we evaluate the mapping accuracy and work efficiency of drone mapping for disaster investigation application through comparing with traditional investigation work process which was dependent on labor-intensive field survey. The resolution ortho-image map of within less 5cm of GSD generated by aerial photos acquired from UAVs at the altitude of 100m–250m enabled us to check damage information such as facilities destroy or the trace of soil erosion around the river flooded and reservoir collapsed area. The photogrammetry-based drone mapping technology for the disaster damage investigation is expected to be an alternative approach to support or replace the labor-intensive disaster site survey that needs to investigate the disaster site quickly and timely.