Shadow Analysis in Assisting Damage Detection Due to Earthquakes from Quickbird Imagery

This study is to take the advantage of shadow appearance in Standard Imagery produced from QuickBird for damage detection in urban areas. In a very complex scene of an urban area acquired from very high resolution satellite-based optical sensors, fortunately, the buildings tend to align in some dominant directions in a small area and posses geometric regularity. Therefore, their shadows also align following these dominant directions in a small area in spite of the acquisition condition. The changes of building structures caused by an earthquake could affect the orientation, shape and size of its shadow. Two QuickBird scenes acquired over the city of Boumerdes, which was one of the most heavily-damaged areas due to the Algeria earthquake of magnitude 6.8 on May 21, 2003, are employed in this study. The first one was about one year before the event (April 22, 2002) and the second one was two days after the event (May 23, 2003). The result shows that the differences in shadow’s lengths paralleling dominant directions can assist the detection of collapsed buildings. Moreover, unlike other classes of land cover in urban areas, the shadows can be successfully segmented by a conventional pixel-based classification method. The promising results from this analysis prove that shadow-based information could be used as a potential cue for automated detection of building damage. * Corresponding author