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

DOI

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.

Identifier
DOI https://doi.org/10.5880/enmap.2023.001
Related Identifier https://eo-college.org/courses/beyond-the-visible-enmap-data-access-and-image-preprocessing-techniques
Related Identifier https://doi.org/10.3390/rs9070676
Related Identifier https://doi.org/10.5281/zenodo.3742909
Related Identifier https://www.enmap.org/
Related Identifier https://enmap.git-pages.gfz-potsdam.de/GFZ_Tools_EnMAP_BOX/EnPT/doc/index.html
Related Identifier https://www.youtube.com/@HYPERedu_GFZ
Related Identifier https://doi.org/10.3390/rs70708830
Related Identifier https://doi.org/10.1016/j.rse.2023.113632
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:7773
Provenance
Creator DLR; ESA
Publisher GFZ Data Services
Contributor Scheffler, Daniel; Brosinsky, Arlena; Förster, Saskia; HYPERedu Team
Publication Year 2023
Funding Reference German Aerospace Center / Federal Ministry for Economic Affairs And Climate Action Germany, 50EE1923
Rights EnMAP data @DLR [2022]; ESA License for COP-DEM-GLO-30-R data; ESA Licence for Sentinel-2 data; https://www.enmap.org/data/resources/EnMAP_Data_License.pdf; https://spacedata.copernicus.eu/documents/20123/121286/CSCDA_ESA_Mission-specific+Annex_31_Oct_22.pdf/fb109818-56ad-bbee-053c-d972aed25ce6?t=1674741175657; https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice
OpenAccess true
Contact HYPERedu Team (GFZ German Research Centre for GeoSciences, Potsdam, Germany)
Representation
Resource Type Dataset
Version 1.0
Discipline Geodesy, Geoinformatics and Remote Sensing
Spatial Coverage (13.135W, 52.452S, 13.459E, 52.777N)