Ensemble classifiers for building damage detection

Each year, numerous disasters cause high amount of human and material losses. With the presence of both technological and social means like very high spatial resolution (VHR) satellite images and the International Charter “Space and Major Disasters” respectively, decision makers can obtain the needed information to make fast life-saving decisions. The automation of parts of the image analysis process is thus of great interest. This is why we propose to apply an ensemble classification method to provide better building damage evaluation using optical images acquired before and after the event. We base this work on our previous framework for fast building detection and damage evaluation by supervised classification. The results show the positive impact of ensemble classifiers in damage mapping.