Datasets:
File size: 3,003 Bytes
fd3f9d6 aaa71f6 fd3f9d6 2318c4c 78e05cf 2318c4c 748ac87 2318c4c b46a5c5 78e05cf b46a5c5 5a036c6 b46a5c5 78e05cf 2318c4c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
license: cc-by-sa-4.0
language:
- en
tags:
- earth-observation
- remote-sensing
- disaster-response
size_categories:
- 1B<n<10B
---
**Overview**
* BRIGHT is the first open-access, globally distributed, event-diverse multimodal dataset specifically curated to support AI-based disaster response.
* It covers five types of natural disasters and two types of man-made disasters across 12 regions worldwide, with a particular focus on developing countries.
* About 4,500 paired optical and SAR images containing over 350,000 building instances in BRIGHT, with a spatial resolution between 0.3 and 1 meters, provides detailed representations of individual buildings.
**IEEE GRSS Data Fusion Contest 2025**
* BRIGHT also serves as the official dataset of [IEEE GRSS DFC 2025 Track II](https://www.grss-ieee.org/technical-committees/image-analysis-and-data-fusion/).
* Please download **dfc25_track2_trainval.zip** and unzip it. It contains training images & labels and validation images for the development phase.
* Please download **dfc25_track2_test.zip** and unzip it. It contains test images for the final test phase.
* Benchmark code related to the DFC 2025 can be found at this [Github repo](https://github.com/ChenHongruixuan/BRIGHT).
* The official leaderboard is located on the [Codalab-DFC2025-Track II](https://codalab.lisn.upsaclay.fr/competitions/21122) page.
**Paper & Reference**
Details of BRIGHT can be refer to our [paper](https://arxiv.org/abs/2501.06019).
If BRIGHT is useful to research, please kindly consider cite our paper
```
@article{chen2025bright,
title={BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response},
author={Hongruixuan Chen and Jian Song and Olivier Dietrich and Clifford Broni-Bediako and Weihao Xuan and Junjue Wang and Xinlei Shao and Yimin Wei and Junshi Xia and Cuiling Lan and Konrad Schindler and Naoto Yokoya},
journal={arXiv preprint arXiv:2501.06019},
year={2025},
url={https://arxiv.org/abs/2501.06019},
}
```
**License**
* Label data of BRIGHT are provided under the same license as the optical images, which varies with different events.
* With the exception of two events, Hawaii-wildfire-2023 and La Palma-volcano eruption-2021, all optical images are from [Maxar Open Data Program](https://www.maxar.com/open-data), following CC-BY-NC-4.0 license. The optical images related to Hawaii-wildifire-2023 are from [High-Resolution Orthoimagery project](https://coast.noaa.gov/digitalcoast/data/highresortho.html) of NOAA Office for Coastal Management. The optical images related to La Palma-volcano eruption-2021 are from IGN (Spain) following CC-BY 4.0 license.
* The SAR images of BRIGHT is provided by [Capella Open Data Gallery](https://www.capellaspace.com/earth-observation/gallery) and [Umbra Space Open Data Program](https://umbra.space/open-data/), following CC-BY-4.0 license.
|