Ebel P., El Baz M., Wang J., Xuan W., Qi H., Zheng Z., Yokoya N., Park J., Park J., Elskens A., Charles E., Modica I., Foltz Z., Bally P., Bossung C., Chini M., Longepe N., Meoni G.
IEEE Geoscience and Remote Sensing Magazine, 2026
Earthquakes are a destructive and oftentimes unanticipated force of nature. To facilitate timely disaster relief, very high-resolution (VHR) spaceborne observations can map urban destruction even over remote or inaccessible terrain. Fostering community-driven innovation on artificial intelligence (AI)-based solutions for rapid mapping of building-level damage, the European Space Agency (ESA) and the International Charter "Space and Major Disasters" jointly organized the "AI for Earthquake Response" competition. The activity was designed to emulate the needs and urges of real postevent activations. In its course, more than 261 teams participated on the ESA Challenges platform and the best-performing AI model accom-plished an overall F1 score of 0.71. This work summarizes the competition's objective, data provided, and outcomes of the challenge. Descriptions for each of the three best-performing AI solutions and their workflows are provided, plus an overview summarizing their recipes for success. We foresee the event and this report as fostering further innovation in the community, working toward data-driven rapid mapping that may in the future support real postseismic activations and save human lives.
