The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2

• URL: http://arxiv.org/abs/2511.05461v1
• Date: Fri, 07 Nov 2025 18:02:07 GMT
• Title: The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2
• Authors: Olivier Dietrich, Merlin Alfredsson, Emilia Arens, Nando Metzger, Torben Peters, Linus Scheibenreif, Jan Dirk Wegner, Konrad Schindler,
• Abstract summary: We investigate whether medium-resolution Earth observation images from the Copernicus program can support building damage assessment.<n>We introduce xBD-S12, a dataset of 10,315 pre- and post-disaster image pairs from both Sentinel-1 and Sentinel-2.<n>In a series of experiments, we demonstrate that building damage can be detected and mapped rather well in many disaster scenarios.
• Score: 23.909180599569158
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Natural disasters demand rapid damage assessment to guide humanitarian response. Here, we investigate whether medium-resolution Earth observation images from the Copernicus program can support building damage assessment, complementing very-high resolution imagery with often limited availability. We introduce xBD-S12, a dataset of 10,315 pre- and post-disaster image pairs from both Sentinel-1 and Sentinel-2, spatially and temporally aligned with the established xBD benchmark. In a series of experiments, we demonstrate that building damage can be detected and mapped rather well in many disaster scenarios, despite the moderate 10$\,$m ground sampling distance. We also find that, for damage mapping at that resolution, architectural sophistication does not seem to bring much advantage: more complex model architectures tend to struggle with generalization to unseen disasters, and geospatial foundation models bring little practical benefit. Our results suggest that Copernicus images are a viable data source for rapid, wide-area damage assessment and could play an important role alongside VHR imagery. We release the xBD-S12 dataset, code, and trained models to support further research.

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