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 Setand Tier3 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