利用哥白尼卫星影像实现灾后建筑损毁快速评估
The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2
- 基于哨兵1号与2号影像构建对齐数据集xbd-s12
- 10米分辨率下仍可有效识别多数灾害场景中的损毁建筑
- 复杂模型在新灾害上泛化差，基础模型更实用
自然灾害需要快速损毁评估以支持人道主义响应。本文研究哥白尼计划提供的中分辨率遥感影像是否可用于建筑损毁评估，弥补高分辨率影像常因覆盖受限而难以获取的不足。我们构建了xbd-s12数据集，包含10,315对灾前灾后影像，分别来自Sentinel-1和Sentinel-2，与现有xbd基准数据集在空间和时间上对齐。实验表明，尽管地面采样距离为10米，仍可在多种灾害场景中较好地检测并绘制建筑损毁情况。此外发现，该分辨率下建筑结构复杂性对性能提升有限：更复杂的模型在未见灾害上泛化能力差，而地理空间基础模型实际收益不大。结果表明，哥白尼影像可作为快速、大范围损毁评估的可靠数据源，可与超高分辨率影像协同使用。相关数据集、代码及训练模型已开源，地址：https://github.com/prs-eth/xbd-s12。
原文摘要 · Abstract (English)
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 .
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