Paper Info
Title
Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery
Abstract
Rapid damage assessment after natural disasters (e.g., earthquakes) and violent conflicts (e.g., war-related destruction) is crucial for initiating effective emergency response actions. Remote-sensing satellites equipped with very high spatial resolution (VHR) multispectral and synthetic aperture radar (SAR) imaging sensors can provide vital information due to their ability to map the affected areas with high geometric precision and in an uncensored manner. In this paper, we present a novel method that detects buildings destroyed in an earthquake using pre-event VHR optical and post-event detected VHR SAR imagery. The method operates at the level of individual buildings and assumes that they have a rectangular footprint and are isolated. First, the 3-D parameters of a building are estimated from the pre-event optical imagery. Second, the building information and the acquisition parameters of the VHR SAR scene are used to predict the expected signature of the building in the post-event SAR scene assuming that it is not affected by the event. Third, the similarity between the predicted image and the actual SAR image is analyzed. If the similarity is high, the building is likely to be still intact, whereas a low similarity indicates that the building is destroyed. A similarity threshold is used to classify the buildings. We demonstrate the feasibility and the effectiveness of the method for a subset of the town of Yingxiu, China, which was heavily damaged in the Sichuan earthquake of May 12, 2008. For the experiment, we use QuickBird and WorldView-1 optical imagery, and TerraSAR-X and COSMO-SkyMed SAR data.
Year
DOI
Venue
2010
10.1109/TGRS.2009.2038274
Geoscience and Remote Sensing, IEEE Transactions
Keywords
Field
DocType
earthquake engineering,earthquakes,remote sensing by radar,structural engineering,synthetic aperture radar,AD 2008 05 12,COSMO-SkyMed SAR data,China,QuickBird imagery,Sichuan earthquake,TerraSAR-X data,VHR SAR imagery,VHR SAR imaging sensors,VHR multispectral imaging sensors,VHR optical imagery,WorldView-1 optical imagery,Yingxiu,buildings,damage detection,data fusion,earthquake damage assessment,geometric precision,multisensor change detection,natural disaster,remote-sensing satellites,synthetic aperture radar,Damage assessment,damage detection,data fusion,multisensor change detection,natural disaster,remote sensing,synthetic aperture radar (SAR),urban areas,very high spatial resolution (VHR) images
Computer vision,Satellite,Synthetic aperture radar,Remote sensing,Multispectral image,Sensor fusion,Footprint,Artificial intelligence,Earthquake engineering,Image resolution,Mathematics,Adaptive optics
Journal
Volume
Issue
ISSN
48
5
0196-2892
Citations 
PageRank 
References 
84
4.35
28
Authors
3
Name
Order
Citations
PageRank
Dominik Brunner117913.67
Guido Lemoine222736.45
Lorenzo Bruzzone34952387.72