Gottfriedsen, Julia Sophia and Berrendorf, Max and Gentine, Pierre and Hassler, Birgit and Reichstein, Markus and Weigel, Katja and 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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Official URL: https://neurips.cc/
Abstract
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.
Item URL in elib: | https://elib.dlr.de/145433/ | ||||||||||||||||||||||||||||||||
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Document Type: | Conference or Workshop Item (Speech, Poster) | ||||||||||||||||||||||||||||||||
Title: | 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" | ||||||||||||||||||||||||||||||||
Authors: |
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Date: | December 2021 | ||||||||||||||||||||||||||||||||
Refereed publication: | No | ||||||||||||||||||||||||||||||||
Open Access: | No | ||||||||||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||||||||||
In SCOPUS: | No | ||||||||||||||||||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||||||||||
Keywords: | Machine Learning, KI, Extreme Events, ERA5 Land, Climate Change | ||||||||||||||||||||||||||||||||
Event Title: | Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) | ||||||||||||||||||||||||||||||||
Event Location: | remote | ||||||||||||||||||||||||||||||||
Event Type: | international Conference | ||||||||||||||||||||||||||||||||
Event Start Date: | 6 December 2021 | ||||||||||||||||||||||||||||||||
Event End Date: | 14 December 2021 | ||||||||||||||||||||||||||||||||
Organizer: | Marc'Aurelio Ranzato, DeepMind | ||||||||||||||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||||||||||||||
DLR - Research theme (Project): | R - Atmospheric and climate research | ||||||||||||||||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||
Institutes and Institutions: | Institute of Atmospheric Physics > Earth System Model Evaluation and Analysis | ||||||||||||||||||||||||||||||||
Deposited By: | Gottfriedsen, Julia Sophia | ||||||||||||||||||||||||||||||||
Deposited On: | 10 Nov 2021 09:46 | ||||||||||||||||||||||||||||||||
Last Modified: | 29 Aug 2024 09:46 |
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