Estimating the Numbers and the Areas of Collapsed Buildings by Combining VHR Images, Statistics and Survey Data: a Case Study of the Lushan Earthquake in China

Abstract

Accurately obtaining the structures and damage types of buildings in earthquake stricken areas is fundamental to supporting rescue forces and estimating economic losses and casualties. As the stricken areas are often much larger than the areas covered by very high resolution (VHR) images, the information obtained from VHR images cannot satisfy practical needs. This study developed a method for estimating the structures and types of damaged buildings by combining VHR images, statistics and ground survey data. First, the rates of damaged buildings with different structures and damage types were manually interpreted from VHR images covering a small part of the stricken area, and further corrected by ground survey data. Second, the corrected rates were reallocated to the seismic intensity zones. Third, the rates in the seismic intensity zones and the statistical data were combined to estimate the numbers and areas of damaged buildings in villages, towns and counties. The presented method was applied to estimate the damages caused by the Lushan earthquake in China. The results indicated that our method can efficiently estimate the amount of the damages and complement existing work on only automatic extracting damaged buildings from VHR images.