Remote sensing technology is a powerful tool to extract regions damaged after an earthquake. There are two methodological approaches in detection of earthquake damage: mono-temporal and multi-temporal. Especially for providing effective emergency management, the monotemporal approach is generally preferred in extraction of earthquake damage as it does not depend on availability of pre-earthquake imagery. For this purpose, a novel method called support vector selection and adaptation (SVSA) has been introduced to detect the damaged regions from a post-earthquake image. In this study, the SVSA method was applied to the region where the Haiti Presidential Palace and Cathedral is located, and the damaged regions were identified. The performance of the SVSA method in identification of the damaged regions was evaluated by comparing the thematic maps obtained by classifying pre- and post-earthquake images. Additionally, the damage patterns for the city of Port-au-Prince were estimated by the SVSA.