BRIGHT is the first open-access, globally distributed, and diverse multimodal global disaster scenario benchmark dataset. It integrates optical imagery and SAR (synthetic aperture radar) data, aiming to support AI-based disaster response. It is widely used in scenarios such as building damage assessment, change detection, remote sensing segmentation, and cross-disaster generalization research, and is used to evaluate the model's ability to detect changes and identify damage in complex environments. This dataset covers 14 regions and 7 types of disasters (5 natural disasters + 2 man-made disasters), containing approximately 4,200 paired image pairs, involving over 380,000 building instances, with a spatial resolution of approximately 0.3–1 meter. The data consists of pre-disaster imagery, post-disaster imagery, and target annotations.