Karslruhe, Germany (2010) - a (hyperspectral) dataset for active participation in the HYPERedu MOOC on forest applications

This dataset accompanying the MOOC on forest applications contains an airborne hyperspectral HyMap image over the study site north of Karlsruhe in Southwest Germany which was recorded in August 2010. The surrounding area of Karlsruhe is characterized by its relatively warm climate due to the influence of the Upper-Rhine and its climate can be considered more continental than typical German conditions. Additionally it is characterized by its flat terrain. Here you can find a diversity of tree species growing in the mixed forests. These include coniferous trees such as Scots Pine, Douglas Fir, Norway Spruce, Silver Fir and Larch as well as deciduous tree species like European Beech, Oak and Red Oak. The image dataset is fully pre-processed –it was atmospherically and topographically corrected by the DLR using ATCOR4 and ORTH software – and provided in TIF format.

In addition to the HyMap image, this dataset contains a point data shapefile with 250 sampling locations, which represents 5 tree species with 50 reference positions each. These reference positions were collected using visual interpretation of high-resolution images in combination with reference tree species maps provided by the local forest administration. These reference tree species maps are also provided as tif-files. The dataset is made publicly available as part of the Massive Open Online Course (MOOC) "Beyond the Visible - Imaging Spectroscopy for Forest Applications ", available from Summer 2025. Guidance on how to derive tree species classification maps using the EnMAP-Box (QGIS plugin) are provided as videos at the HYPERedu YouTube channel, the forest MOOC course pages and the regression workflow documentation.

HYPERedu is an education initiative within the Environmental Mapping and Analysis Program (EnMAP), a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extracting geochemical, biochemical and biophysical variables, which provide information on the status and evolution of various terrestrial and aquatic ecosystems.

本数据集为森林应用领域大规模开放在线课程（Massive Open Online Course，以下简称MOOC）的配套资源，包含2010年8月拍摄的德国西南部卡尔斯鲁厄北部研究区域的机载高光谱HyMap影像。卡尔斯鲁厄周边受上莱茵河区域影响，气候相对温暖，整体大陆性特征相较于德国典型气候更为显著，同时该区域地势平坦开阔。区域内的混交林生长着丰富多样的林木树种，其中针叶树种涵盖欧洲赤松、花旗松、挪威云杉、银杉与落叶松，阔叶树种则包括欧洲山毛榉、栎树及红栎。本影像数据集已完成全流程预处理：德国宇航中心（Deutsches Zentrum für Luft- und Raumfahrt，简称DLR）借助ATCOR4与ORTH软件完成了大气校正与地形校正，最终以TIF格式对外提供。

除HyMap影像外，本数据集还包含一份包含250个采样点位的点数据形状文件，涵盖5个林木树种，每个树种对应50个参考采样点位。上述参考采样点位通过对高分辨率影像进行目视解译，并结合当地林业管理部门提供的林木树种参考图获取。前述林木树种参考图同样以TIF格式提供。本数据集将作为《超越可见光——林业应用成像光谱学》大规模开放在线课程的配套资源，于2025年夏季正式上线发布。

关于如何使用EnMAP-Box（QGIS插件）生成林木树种分类图的操作指南，已以视频形式发布于HYPERedu的YouTube频道、林业MOOC课程页面及回归工作流文档中。HYPERedu是德国高光谱卫星任务“环境制图与分析计划（Environmental Mapping and Analysis Program，简称EnMAP）”下属的教育项目，EnMAP旨在全球范围内开展地球环境的监测与表征工作。EnMAP通过提取地球化学、生物化学及生物物理变量，对地球生态系统的关键动态过程进行测量与建模，这些变量可为各类陆地与水生生态系统的状态及演化过程提供数据支撑。