AUTOMATIC ROAD DAMAGE DETECTION USING HIGH-RESOLUTION SATELLITE IMAGES AND ROAD MAPS

Roads are traffic lifelines for emergency rescue and disaster relief. After major earthquakes, it is very significant to extract road damage rapidly and accurately in disaster areas by remote sensing for emergency rescue. Because road damage caused by earthquake is ever-changing, there is no common spectral characteristic of it in remote sensing images. Meanwhile, there are many phenomena of "synonyms spectrums" and "different spectrum characteristics with the same object" in remote sensing images. Thus, traditional methods by spectrum characteristics are usually with low accuracy and not universal. This paper proposes an automatic approach to extract road damage rapidly based on sidelines using high resolution satellites images and road maps. Road sideline is one of stable geometric features in both pre-earthquake and post-earthquake images, and the change of road sideline is a remarkable evidence of road damage exists. The approach firstly extracts sidelines of undamaged road from images acquired after earthquakes, and then these road sidelines are compared with the road lines before earthquakes supplied by road maps. The damaged segments can be extracted through comparison. The performance of the method is evaluated by an experiment with QuickBird images in the WenChuan earthquake disaster area.