Abstract
Abstract. In this paper, a novel approach is presented that applies multiple overlapping UAV imagesto building damage detection. Traditional building damage detection method focus on 2D changes detection (i.e., those only in image appearance), whereas the 2D information delivered by the images is often not sufficient and accurate when dealing with building damage detection. Therefore the detection of building damage in 3D feature of scenes is desired. The key idea of 3D building damage detection is the 3D Change Detection using 3D point cloud obtained from aerial images through Structure from motion (SFM) techniques. The approach of building damage detection discussed in this paper not only uses the height changes of 3D feature of scene but also utilizes the image's shape and texture feature. Therefore, this method fully combines the 2D and 3D information of the real world to detect the building damage. The results, tested through field study, demonstrate that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and suited well for rapid damage assessment after natural disasters.
Highlights
In recent years, the reported occurrences of natural disasters, such as earthquakes, floods, tsunamis, and mud-rock flow, are on the rise, leading to increased public awareness of the impact of catastrophic events, such as the 2008 Wenchuan earthquake, the 2010 Chile earthquake, the 2011 Japan tsunami and the 2013 Ya'an earthquake
We have proposed and tested the 2003 Northern Algeria Earthquake,” Proceedings techniques for image registration, building extraction, 13th world Conference on earthquake Engineering, change detection and damage detection
The results, Chiroiu and, L., André, G., “Damage assessment using evaluated on real data, demonstrate that this method is high resolution satellite imagery: application to 2001 feasible and effective in building damage detection
Summary
The reported occurrences of natural disasters, such as earthquakes, floods, tsunamis, and mud-rock flow, are on the rise, leading to increased public awareness of the impact of catastrophic events, such as the 2008 Wenchuan earthquake, the 2010 Chile earthquake, the 2011 Japan tsunami and the 2013 Ya'an earthquake. Building as a shelter is an essential place for human, estimating building damage due to natural disasters in real-time and scenario mode is becoming more necessary as emergency response and reconstruction after the disasters. It is important to detect the building damage from the remote sensing image for estimating building damage. Researches have proposed many building damage detection algorithms using remote sensing technology for estimating building damage. Most of them consider the detection of 2D changes to detect the building damage(Brunner et al, 2010; Thomas, 2010; Chesnel et al, 2008; Turker et al, 2005; Rathje et al, 2004; Chiroiu et al, 2002),several studies make use of the 3D information of scenes to detect the building damage(Liu et al.,2013;Dong et al, 2013; Rezaeian, 2012; Taneja et al, 2012; Turker, 2005;).At present, detecting buildings damaged by using 3D feature of scene mainly makes use of the height information of Lidar data and 3D GIS model. LIDAR data and 3D GIS are difficult to get
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