Requena-Mesa, Christian und Benson, Vitus und Reichstein, Markus und Runge, Jakob und Denzler, Joachim (2021) EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021. CVPR EarthVision Workshop, 2021-06-19, Online. doi: 10.1109/CVPRW53098.2021.00124. ISSN 2160-7508.
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Kurzfassung
Satellite images are snapshots of the Earth surface. We propose to forecast them. We frame Earth surface forecasting as the task of predicting satellite imagery conditioned on future weather. EarthNet2021 is a large dataset suitable for training deep neural networks on the task. It contains Sentinel 2 satellite imagery at 20 m resolution, matching topography and mesoscale (1.28 km) meteorological variables packaged into 32000 samples. Additionally we frame EarthNet2021 as a challenge allowing for model intercomparison. Resulting forecasts will greatly improve (> ×50) over the spatial resolution found in numerical models. This allows localized impacts from extreme weather to be redicted, thus supporting downstream applications such as crop yield prediction, forest health assessments or biodiversity monitoring. Find data, code, and how to participate at www.earthnet.tech.
elib-URL des Eintrags: | https://elib.dlr.de/145613/ | ||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||
Titel: | EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task | ||||||||||||||||||||||||
Autoren: |
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Datum: | 2021 | ||||||||||||||||||||||||
Erschienen in: | 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 | ||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||
DOI: | 10.1109/CVPRW53098.2021.00124 | ||||||||||||||||||||||||
ISSN: | 2160-7508 | ||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||
Stichwörter: | Earth surface forecasting, dataset, challenge | ||||||||||||||||||||||||
Veranstaltungstitel: | CVPR EarthVision Workshop | ||||||||||||||||||||||||
Veranstaltungsort: | Online | ||||||||||||||||||||||||
Veranstaltungsart: | Workshop | ||||||||||||||||||||||||
Veranstaltungsdatum: | 19 Juni 2021 | ||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||
HGF - Programmthema: | keine Zuordnung | ||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||
DLR - Forschungsgebiet: | R - keine Zuordnung | ||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - keine Zuordnung | ||||||||||||||||||||||||
Standort: | Jena | ||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Datenwissenschaften > Datenmanagement und Analyse | ||||||||||||||||||||||||
Hinterlegt von: | Käding, Christoph | ||||||||||||||||||||||||
Hinterlegt am: | 18 Nov 2021 15:56 | ||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:44 |
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