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--- |
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language: |
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- en |
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license: cc-by-sa-4.0 |
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task_categories: |
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- image-segmentation |
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size_categories: |
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- 1B<n<10B |
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tags: |
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- earth-observation |
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- remote-sensing |
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- disaster-response |
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--- |
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**Overview** |
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* BRIGHT is the first open-access, globally distributed, event-diverse multimodal dataset specifically curated to support AI-based disaster response. |
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* It covers five types of natural disasters and two types of man-made disasters across 14 regions worldwide, with a particular focus on developing countries. |
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* About 4,200 paired optical and SAR images containing over 380,000 building instances in BRIGHT, with a spatial resolution between 0.3 and 1 meters, provides detailed representations of individual buildings. |
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<p align="center"> |
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<img src="./overall.jpg" alt="accuracy" width="97%"> |
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</p> |
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**Benchmark for building damage assessment** |
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* Please download **pre-event.zip**, **post-event.zip**, and **target.zip**. Note that for the optical pre-event data in Ukraine, Myanmar, and Mexico, please follow our [instructions/tutorials](https://github.com/ChenHongruixuan/BRIGHT/blob/master/tutorial.md) to download. |
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* For the benchmark code and evaluation protocal for supervised building damage assessment, cross-event transfer, and unsupervised multimodal change detection, please see our [Github repo](https://github.com/ChenHongruixuan/BRIGHT). |
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* You can download models' checkpoints in this [repo](https://zenodo.org/records/15349462). |
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**Unsupervised multimodal image matching** |
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* BRIGHT supports the evaluation of Unsupervised Multimodal Image Matching (UMIM) algorithms for their performance in large-scale disaster scenarios. Please download data with the prefix "**umim**", such as **umim_noto_earthquake.zip**, and use our [code](https://github.com/ChenHongruixuan/BRIGHT) to test the exsiting algorithms' performance. |
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**IEEE GRSS Data Fusion Contest 2025 (Closed, All Data Available)** |
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* 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/). Now, DFC 25 is over. We recommend using the full version of the dataset along with the corresponding split names provided in our [Github repo](https://github.com/ChenHongruixuan/BRIGHT). Yet, we also retain the original files used in DFC 2025 for download. |
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* Please download **dfc25_track2_trainval.zip** and unzip it. It contains training images & labels and validation images for the development phase. |
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* Please download **dfc25_track2_test.zip** and unzip it. It contains test images for the final test phase. |
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* Please download **dfc25_track2_val_labels.zip** for validation labels, redownload **dfc25_track2_test_new.zip** for test images with geo-coordinates and **dfc25_track2_test_labels.zip** for testing labels. |
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* Benchmark code related to the DFC 2025 can be found at this [Github repo](https://github.com/ChenHongruixuan/BRIGHT). |
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* The official leaderboard is located on the [Codalab-DFC2025-Track II](https://codalab.lisn.upsaclay.fr/competitions/21122) page. |
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**Paper & Reference** |
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Details of BRIGHT can be refer to our [paper](https://huggingface.co/papers/2501.06019). |
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If BRIGHT is useful to research, please kindly consider cite our paper |
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``` |
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@article{chen2025bright, |
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title={BRIGHT: A globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response}, |
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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}, |
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journal={arXiv preprint arXiv:2501.06019}, |
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year={2025}, |
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url={https://arxiv.org/abs/2501.06019}, |
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} |
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``` |
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**License** |
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* Label data of BRIGHT are provided under the same license as the optical images, which varies with different events. |
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* 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. |
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* 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. |
