Gottfriedsen, Julia Sophia und Berrendorf, Max und Gentine, Pierre und Hassler, Birgit und Reichstein, Markus und Weigel, Katja und Eyring, Veronika (2021) On the Generalization of Agricultural Drought Classification from Climate Data. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) Workshop 2021 "Tackling Climate Change with Machine Learning". Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021-12-06 - 2021-12-14, remote.
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Offizielle URL: https://neurips.cc/
Kurzfassung
Climate change is expected to increase the likelihood of drought events, with severe implications for food security. Unlike other natural disasters, droughts have a slow onset and depend on various external factors, making drought detection in climate data difficult. In contrast to existing works that rely on simple relative drought indices as ground-truth data, we build upon SMI from a hydrological model, which is directly related to insufficiently available water to vegetation. Given ERA5-Land climate input data of six months with landuse information from MODIS satellite observation, we compare different models with and without sequential inductive bias in their ability to classify droughts based on SMI. We use PR-AUC and Macro F1 Score as evaluation measures to account for the class imbalance and obtain promising results despite a challenging time-based split. We show in an ablation study that the models retain their predictive capabilities given input data of coarser resolutions, as frequently encountered in climate models.
elib-URL des Eintrags: | https://elib.dlr.de/145433/ | ||||||||||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag, Poster) | ||||||||||||||||||||||||||||||||
Titel: | On the Generalization of Agricultural Drought Classification from Climate Data. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) Workshop 2021 "Tackling Climate Change with Machine Learning" | ||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | Dezember 2021 | ||||||||||||||||||||||||||||||||
Referierte Publikation: | Nein | ||||||||||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||
Stichwörter: | Machine Learning, KI, Extreme Events, ERA5 Land, Climate Change | ||||||||||||||||||||||||||||||||
Veranstaltungstitel: | Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) | ||||||||||||||||||||||||||||||||
Veranstaltungsort: | remote | ||||||||||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||||||||||
Veranstaltungsbeginn: | 6 Dezember 2021 | ||||||||||||||||||||||||||||||||
Veranstaltungsende: | 14 Dezember 2021 | ||||||||||||||||||||||||||||||||
Veranstalter : | Marc'Aurelio Ranzato, DeepMind | ||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Atmosphären- und Klimaforschung | ||||||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Physik der Atmosphäre > Erdsystemmodell -Evaluation und -Analyse | ||||||||||||||||||||||||||||||||
Hinterlegt von: | Gottfriedsen, Julia Sophia | ||||||||||||||||||||||||||||||||
Hinterlegt am: | 10 Nov 2021 09:46 | ||||||||||||||||||||||||||||||||
Letzte Änderung: | 29 Aug 2024 09:46 |
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