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

DLR,; ESA,

doi:10.5880/ENMAP.2023.001

Datensatz

DATENSATZ AKTIONENEXPORT

Zur Ablage hinzufügen

Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben

Datenpublikation

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

Urheber*innen

DLR,
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

ESA,
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

/persons/resource/danschef

Scheffler, D.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

/persons/resource/abros

Brosinsky, Arlena
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

/persons/resource/foerster

Förster, S.
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Team, HYPERedu
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Externe Ressourcen

Es sind keine externen Ressourcen hinterlegt

Volltexte (frei zugänglich)

Es sind keine frei zugänglichen Volltexte in GFZpublic verfügbar

Ergänzendes Material (frei zugänglich)

Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar

Zitation

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

Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5023154

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).