  As one of the most destructive disasters in the world, earthquake causes
death, injuries, destruction and enormous damage to the affected area. It is
significant to detect buildings after an earthquake in response to
reconstruction and damage evaluation. In this research, we proposed an
automatic rooftop detection method based on the convolutional neural network
(CNN) to extract buildings in the city of Christchurch and tuned
hyperparameters to detect small detached houses from the aerial image. The
experiment result shows that our approach can effectively and accurately detect
and segment buildings and has competitive performance.
