Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 291-294, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-291-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 291-294, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-291-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

Rapid Disaster Mapping through Data Integration from UAVs and Multi-sensors Mounted on Investigation Platforms of NDMI, Korea

S. S. Kim1, S. H. Yoo2, J. S. Park1, S. B. Cho1, and T. H. Kim1 S. S. Kim et al.
  • 1National Disaster Management research Institute, 365 Jongga-ro, Jung-gu, Ulsan, 44538, Rep. of Korea
  • 2Yonsei university, 50 yonsei-ro, Seodaemun-gu, Seoul, 03722, Rep. of Korea

Keywords: Rapid Disaster Mapping, Data Integration, UAVs, MMS, Multi-sensors

Abstract. As the recent disaster is so difficult to predict when and where it would hit, so it requires paradigm for disaster shifts from response to preparedness. In order to respond this change, NDMI has studied disaster scientific investigation (DSI) technologies for revealing systematically the root cause of disaster and protecting repetitive recurrence.
The purpose of this study is to propose a convergence approach between data acquired from different types of sensors on a van-type investigation platform and UAVs of NDMI and assess their applicability for timely natural and man-made disaster mapping and monitoring. In order to evaluate its applicability for rapid disaster mapping, we pre-tested the proposed approach for NDMI site in Ulsan, Korea. For the enhancement of the direct geo-referencing accuracy of UAV imagery captured from on-board camera of DJI and the creation of more accurate map products, camera IOPs refinement and bundle adjustment were also performed with minimal GCPs. Finally, we conducted UAV data registration with LiDAR point clould for disaster mapping applications.