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

TL;DR

This study explores the use of medium-resolution Copernicus satellite images from Sentinel-1 and Sentinel-2 for rapid building damage assessment after disasters, demonstrating their potential to complement high-resolution imagery.

Contribution

Introduces the xBD-S12 dataset of aligned pre- and post-disaster satellite image pairs and evaluates their effectiveness for damage detection, highlighting the practicality of medium-resolution data.

Findings

Building damage can be detected effectively at 10m resolution.

Complex model architectures do not significantly improve damage mapping.

Copernicus images are viable for rapid, wide-area damage assessment.

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 at https://github.com/prs-eth/xbd-s12 .