OpenEarthMap-SAR: A Benchmark Synthetic Aperture Radar Dataset for Global High-Resolution Land Cover Mapping

Overview: OpenEarthMap-SAR is a benchmark synthetic aperture radar dataset, for global high-resolution land cover mapping. It consists of 5033 images covering 35 regions from Japan, France and USA, with partically manually annotated and fully pesudo 8-class land cover labels at a 0.15–0.5m ground sampling distance. IEEE GRSS Data Fusion Contest 2025 OpenEarthmap-SAR also serves as the official dataset of IEEE GRSS DFC 2025 Track I. Please download dfc25_track1_trainval.zip and unzip it. It contains training images & labels and validation images. Please download dfc25_track1_test.zip and unzip it. It contains test images. Please download dfc25_track1_val_labels.zip and dfc25_track1_test_labels.zip and unzip them It contains the labels of val and test images. Benchmark code related to the DFC 2025 can be found at this Github repo. The official leaderboard is located on the Codalab-DFC2025-Track I page. Paper & Reference Details of OpenEarthMap-SAR can be refer to our paper. If OpenEarthMap-SAR is useful to research, please kindly consider cite our paper @article{xia2025openearthmapsar, title={OpenEarthMap-SAR: A Benchmark Synthetic Aperture Radar Dataset for Global High-Resolution Land Cover Mapping}, author={Junshi Xia and Hongruixuan Chen and Clifford Broni-Bediako and Yimin Wei and Jian Song and Naoto Yokoya}, year={2025}, journal={IEEE Geoscience and Remote Sensing Magazine}, } License of Track 1Optical images are provided by the National Institute of Geographic and Forest Information (IGN), France, under the CC BY 2.0 license, with contributions from the Geospatial Information Authority of Japan (GSI) and the National Agriculture Imagery Program (NAIP), USA. SAR images are supplied by the Umbra Open Data Program under the CC BY 4.0 license. Label datasets are shared under the same license as the original optical images, with specific terms varying by source dataset.概述： OpenEarthMap-SAR是一款面向全球高分辨率土地覆盖制图的基准合成孔径雷达（Synthetic Aperture Radar, SAR）数据集。该数据集包含5033幅图像，覆盖日本、法国与美国的35个区域，配有部分人工标注且全部为伪标注的8类土地覆盖标签，地面采样距离为0.15–0.5米。 IEEE地理科学与遥感学会（IEEE Geoscience and Remote Sensing Society, GRSS）2025年数据融合竞赛 OpenEarthMap-SAR同时作为IEEE GRSS 2025年数据融合竞赛赛道一（Track I）的官方数据集。 请下载dfc25_track1_trainval.zip并解压，该压缩包包含训练图像与标签，以及验证图像。 请下载dfc25_track1_test.zip并解压，该压缩包包含测试图像。 请下载dfc25_track1_val_labels.zip与dfc25_track1_test_labels.zip并解压，二者分别包含验证集与测试集图像的标签。 与2025年数据融合竞赛相关的基准代码可在该GitHub仓库中获取。 官方排行榜位于Codalab平台的DFC2025赛道一页面。 论文与参考文献 OpenEarthMap-SAR的详细信息可参阅我们的学术论文。 若OpenEarthMap-SAR对您的研究有所助益，请考虑引用我们的论文： @article{xia2025openearthmapsar, title={OpenEarthMap-SAR: A Benchmark Synthetic Aperture Radar Dataset for Global High-Resolution Land Cover Mapping}, author={Junshi Xia and Hongruixuan Chen and Clifford Broni-Bediako and Yimin Wei and Jian Song and Naoto Yokoya}, year={2025}, journal={IEEE Geoscience and Remote Sensing Magazine}, } 赛道一授权说明 光学图像由法国国家地理与森林研究所（National Institute of Geographic and Forest Information, IGN）提供，采用CC BY 2.0许可协议；日本地理空间信息局（Geospatial Information Authority of Japan, GSI）与美国国家农业影像计划（National Agriculture Imagery Program, NAIP）亦有贡献。 合成孔径雷达（SAR）图像由Umbra开放数据计划（Umbra Open Data Program）提供，采用CC BY 4.0许可协议。 标签数据集采用与原始光学图像一致的许可协议，具体条款因源数据集而异。