Extraction of collapsed buildings from a pair of Lidar data taken before and after the 2016 Kumamoto, Japan, earthquake was conducted. Lidar surveys were carried out for the affected areas along the causative faults by Asia Air Survey Co., Ltd. The density of the collected Lidar data was 1.5 - 2 points/m2 for the first flight on April 15, 2016 and 3 - 4 points/m2 for the second flight on April 23, 2016. The spatial correlation coefficient of the two Lidar data was calculated using a 101 x 101 pixels window (50 m x 50 m), and the horizontal shift of the April-23 digital surface model (DSM) with the maximum correlation coefficient was considered as the crustal movement by the April-16 main-shock. The horizontal component of the calculated coseismic displacement was applied to the post-event DSM to cancel it, and then the vertical displacement between the two DSMs was calculated. The both horizontal and vertical coseismic displacements were removed to extract collapsed buildings. Then building-footprints were employed to assess the changes of the DSMs within them. The average of difference between the pre- and post-event DSMs within a building footprint was selected as a parameter to evaluate whether a building is collapsed or not. The extracted height difference was compared with the spatial coherence value calculated from pre- and post-event ALOS-2 PALSAR-2 data and the result of field damage surveys. Based on this comparison, the collapsed buildings could be extracted well by setting a proper threshold value for the average height difference.
Fumio Yamazaki, Luis Moya, and Wen Liu, "Use of multitemporal lidar data to extract changes due to the 2016 Kumamoto earthquake," Proc. SPIE 10431, Remote Sensing Technologies and Applications in Urban Environments II, 104310B (Presented at SPIE Remote Sensing: September 12, 2017; Published: 4 October 2017); https://doi.org/10.1117/12.2278061.
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