2013 Simulated EnMAP Mosaics for the San Francisco Bay Area, USA

Cooper, S.; Okujeni, A.; Jänicke, C.; Segl, K.; van der Linden, S.; Hostert, P.

doi:10.2312/enmap.2020.002

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2013 Simulated EnMAP Mosaics for the San Francisco Bay Area, USA

Urheber*innen

Cooper, S.
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Okujeni, A.
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Jänicke, C.
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

/persons/resource/segl

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

van der Linden, S.
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Hostert, P.
EnMAP - The Environmental Mapping and Analysis Program, External Organizations;

Externe Ressourcen

https://doi.org/10.5880/EnMAP.2020.002
(Ergänzendes Material)

https://doi.org/10.1016/j.rse.2020.111856
(Ergänzendes Material)

Volltexte (frei zugänglich)

EnMAP_TechnicalReport_2013BayArea_final.pdf
(Verlagsversion), 6MB

Ergänzendes Material (frei zugänglich)

Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar

Zitation

Cooper, S., Okujeni, A., Jänicke, C., Segl, K., van der Linden, S., Hostert, P. (2020): 2013 Simulated EnMAP Mosaics for the San Francisco Bay Area, USA, (EnMAP Technical Report), Potsdam : GFZ Data Services, 15 p.
https://doi.org/10.2312/enmap.2020.002

Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5002054

Zusammenfassung

This dataset is composed of simulated EnMAP mosaics for the San Francisco Bay Area, USA. Hyperspectral imagery used for the EnMAP simulation was collected across three time periods (Spring, Summer, and Fall) in 2013 with the AVIRIS-Classic sensor flown as part of the HyspIRI Preparatory Campaign. Flight lines were simulated to EnMAP-like data using the EnMAP end-to end Simulation tool to produce 30 x 30 m imagery with 195 bands (after band removal) ranging from 423 to 2439 nm. Secondary geometric correction was applied using automatically generated tie points, and a class-wise empirical across track brightness correction was implemented to mitigate brightness gradients.