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

DLR, ESA (2023): Berlin as seen by EnMAP - a (hyperspectral) dataset for active participation in the HYPERedu MOOC on preprocessing techniques.
https://doi.org/10.5880/ENMAP.2023.001

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 Urheber:
DLR1, Autor
ESA1, Autor
Scheffler, D.1, 2, Beitragender              
Brosinsky, Arlena1, 2, Beitragender              
Förster, S.1, 2, Beitragender              
Team, HYPERedu1, Beitragender
Affiliations:
1EnMAP - The Environmental Mapping and Analysis Program, External Organizations, ou_1303888              
21.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146028              

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Schlagwörter: hyperspectral, hyperspectral imagery, imaging spectroscopy, EnMAP, Sentinel-2, Berlin, preprocessing, DEM
 Zusammenfassung: 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).

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Sprache(n): eng - Englisch
 Datum: 20232023
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: Potsdam : GFZ Data Services
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.5880/ENMAP.2023.001
GFZPOF: p4 T5 Future Landscapes
GFZPOFCCA: p4 CARF RemSens
 Art des Abschluß: -

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