Berlin as seen by EnMAP - a (hyperspectral) dataset for active participation in the HYPERedu MOOC on preprocessing techniques

2026-05-27T22:59:20Zhttp://doidb.wdc-terra.org/oaip/oai

oai:doidb.wdc-terra.org:77732025-02-26T09:12:00ZDOIDBDOIDB.ENMAP

false4DOIDB.ENMAP 10.5880/enmap.2023.001 DLR German Aerospace Center ESA European Space Agency Berlin as seen by EnMAP - a (hyperspectral) dataset for active participation in the HYPERedu MOOC on preprocessing techniques GFZ Data Services 2023 hyperspectral hyperspectral imagery imaging spectroscopy EnMAP Sentinel-2 Berlin preprocessing DEM Earth Observation Satellites Scheffler, Daniel Daniel Scheffler GFZ German Research Centre for GeoSciences, Potsdam, Germany Brosinsky, Arlena Arlena Brosinsky 0000-0001-9974-8497 GFZ German Research Centre for GeoSciences, Potsdam, Germany Förster, Saskia Saskia Förster 0000-0001-7752-7394 GFZ German Research Centre for GeoSciences, Potsdam, Germany HYPERedu Team GFZ German Research Centre for GeoSciences, Potsdam, Germany 2022-07-24 2022-07-24T10:45:21/2022-07-24T10:45:26 2022-07-24T10:45:21U/2022-07-24T10:45:26U Dataset https://eo-college.org/courses/beyond-the-visible-enmap-data-access-and-image-preprocessing-techniques 10.3390/rs9070676 10.5281/zenodo.3742909 https://www.enmap.org/ https://enmap.git-pages.gfz-potsdam.de/GFZ_Tools_EnMAP_BOX/EnPT/doc/index.html https://www.youtube.com/@HYPERedu_GFZ 10.3390/rs70708830 10.1016/j.rse.2023.113632 1.0 EnMAP data @DLR [2022] ESA License for COP-DEM-GLO-30-R data ESA Licence for Sentinel-2 data The dataset contains a spaceborne hyperspectral image acquired by EnMAP over Berlin, Germany, and surrounding areas on July 24th, 2022. The data was preprocessed to Level 1B format (systematically and radiometrically corrected) and is provided in separate BSQ files for the VNIR and SWIR sensor of the instrument, respectively. The Level 1B product is accompanied by a history file (xml), a metadata file (xml), six quality masks (cirrus, classes, cloud, cloud shadow, haze and snow) as well as quality test flags and pixel masks for the VNIR and SWIR files separately (all TIF format).

In addition, this dataset comes with a digital elevation model, COP-DEM-GLO-30-R (ESA, Copernicus) and a Sentinel-2 scene (ESA, Copernicus) as references for geometric and atmospheric correction with the EnMAP processing tool (EnPT). Please note that the two datasets described above are NOT part of the same license as the EnMAP data.

The dataset is made publicly available as part of the Massive Open Online Course (MOOC) "Beyond the Visible - EnMAP data access and image preprocessing techniques", available from July 2023.

Guidance on preprocessing hyperspectral imagery in general, access to EnMAP data and a hands-on tutorial on preprocessing of EnMAP data with EnPT in the EnMAP-Box (QGIS plugin) are provided as videos at the HYPERedu YouTube channel, the MOOC course page and the EnPT documentation. More information about the EnMAP mission can be found on the mission website and in Guanter et al. (2016) and Storch et al. (2023).

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.
13.1349 13.4586 52.7768 52.4519 German Aerospace Center / Federal Ministry for Economic Affairs And Climate Action Germany 50EE1923 ENVAL - Wissenschaftliche Nutzungsvorbereitung und Unterstützung der hyperspektralen Satellitenmission EnMAP