 This paper proposes a new semi-supervised classification approach for identifying urban changes caused by an earthquake. It uses a combination of labeled data, ground motion and fragility functions to accurately detect affected areas. This method has been tested on the 2023 Turkey earthquake sequence and achieved an accuracy of 81%, demonstrating its potential for rapid damage assessment in the aftermath of large-magnitude earthquakes. This article was authored by Imar Portillo and Luis Moya.