Pan-European dataset for glacier facies classification

The dataset includes 138273 manually annotated point labels and the corresponding image stacks collected on 92 Landsat and Sentinel-2 scenes covering 31 glaciers across the Alps, Pyrenees, Scandinavia, Iceland and Svalbard. Eight surface classes are provided: ice, snow, firn, debris, superimposed ice, shadow, cloud and water. Labels were produced by three expert glaciologists and refined through a cross-check procedure involving harmonisation of ambiguous transitions and addition of points in sparsely sampled areas. Pre- and post-cross-check label sets are included, along with acquisition metadata to facilitate reproducibility. The dataset is intended as a benchmark for automated glacier facies mapping and for developing machine learning or remote sensing algorithms under diverse glaciological and radiometric conditions. Please cite the accompanying paper when using these data. To cite this dataset, please follow the instructions at https://github.com/konstantin-a-maslov/glacier_facies_classification本数据集包含138273条人工标注的点标签，以及采集自92景Landsat与Sentinel-2影像的对应影像栈，覆盖阿尔卑斯山脉、比利牛斯山脉、斯堪的纳维亚半岛、冰岛以及斯瓦尔巴群岛的31处冰川。数据集共包含8种地表类别：冰、积雪、粒雪（firn）、碎屑物、叠加冰（superimposed ice）、阴影、云与水体。标签由三位冰川学专家制作，并通过交叉校验流程进行优化：该流程包括统一模糊边界的类别归属，以及在采样稀疏区域补充标注点。数据集同时提供交叉校验前与校验后的标签集，以及影像采集元数据，以保障研究的可复现性。 本数据集旨在作为自动化冰川相制图，以及在多样冰川学与辐射测量条件下开发机器学习或遥感算法的基准数据集。使用本数据集时，请引用随附的学术论文。如需引用该数据集，请遵循以下链接中的指引：https://github.com/konstantin-a-maslov/glacier_facies_classification