Three-dimensional, km-scale hyperspectral data of a well-exposed Zn-Pb mineral exploration target at Black Angel Mountain, Greenland

Hyperspectral imaging is a most promising innovative technology for non-invasive material mapping and is starting to be adapted in a wide range of applications, including geosciences, ag-riculture, and food quality control. Novel processing workflows have revolutionized the way we can correct, interpret, and integrate hyperspectral data in the past decade. The reprojection of planar hyperspectral scans to real 3D point cloud representations (“hyperclouds”) has opened up new possibilities for the mapping of large and topographically complex targets. So far, only a few tools have been developed to process and visualize this kind of data. In this contribution we pre-sent an open-source hypercloud dataset capturing complex but spectacularly well exposed geolo-gy from the Black Angel Mountain in Maarmorilik, West Greenland, alongside a detailed and interactive tutorial documenting the workflow that was used to create it.高光谱成像（hyperspectral imaging）是一项极具应用前景的非侵入式物质测绘创新技术，目前已在地球科学、农业、食品质量检测等诸多领域得到广泛应用。近十年来，新型处理流程彻底革新了高光谱数据的校正、解译与集成方式。将平面高光谱扫描数据重投影为真实三维点云表示（hyperclouds，即“超云”）的技术，为大型地形复杂目标的测绘开辟了全新可能。截至目前，针对此类数据的处理与可视化工具仍寥寥无几。本项研究中发布了一套开源超云（hyperclouds）数据集，其采集自西格陵兰玛莫里利克地区黑天使山出露完整、形态壮观的复杂地质构造，同时附带一份详细的交互式教程，完整记录了该数据集的构建工作流。