In February this year, a devastating earthquake occurred in the border zone of Turkey and Syria. This earthquake caused enormous damage in both countries and according to media reports, more than 50,000 people have died (JP, ENG). Even now (as of March of 2023) the aftershocks continue, and millions of people are evacuated due to collapsed buildings. In the event of such a large-scale disaster, it is important to quickly identify the affected areas, which have destroyed buildings or infrastructure. Earth observation satellites enable us to capture images of large regions, even when local infrastructure does not exist or is no longer usable. Therefore, we investigated whether the affected areas can be detected from high-resolution satellite images using machine learning algorithms.