The xBD dataset is the first building damage assessment dataset to date and is one of the largest and highest quality public datasets of annotated high-resolution satellite imagery. **The dataset contains 22,068 images, all of which are 1024*1024 high-resolution satellite remote sensing images, marked with 19 different events.**Including earthquakes, floods, wildfires, volcanic eruptions and car accidents. These images include pre-disaster and post-disaster images, and the images can be used to construct two tasks: positioning and damage assessment. Publishing Agency: Maxar/DigitalGlobe Open Data Initiative **Quantity included:**22068 images **Data format:**png **Data size:**30.3 GB Update time:August 2020 The dataset includes Train training set, Test test set, Holdout Keep SetandTier3 Dataset:

• TrainImage pairs (before and after the disaster) and ground truth information about buildings and damage extent were provided for the pixel segmentation task.
• TestImages only, for challenge ranking purposes;
• HoldoutIt will be kept confidential during the challenge, with the purpose of testing the generalization performance of the results submitted by the verified challenge teams;
• Tier3 DatasetAvailable midway through the challenge and as additional/supplemental training sets covering additional hazard spans and geographic areas. Related Papers:Building Disaster Damage Assessment in Satellite Imagery with Multi-Temporal Fusion