Toward a Collective Agenda on AI for Earth Science Data Analysis

Devis Tuia; Ribana Roscher; Jan Dirk Wegner; Nathan Jacobs; Xiaoxiang Zhu; Gustau Camps-Valls

doi:10.1109/MGRS.2020.3043504

Toward a Collective Agenda on AI for Earth Science Data Analysis

Devis Tuia, Ribana Roscher, Jan Dirk Wegner, Nathan Jacobs, Xiaoxiang Zhu, Gustau Camps-Valls

Computer Science

Research output: Contribution to journal › Review article › peer-review

79 Scopus citations

Abstract

In past years, we have witnessed the fields of geosciences and remote sensing and artificial intelligence (AI) become closer. Thanks to the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to help advance the modeling and understanding of the Earth system. Despite such great opportunities, we have also observed a worrisome tendency to remain in disciplinary comfort zones, applying recent advances from AI on well-resolved remote sensing problems. Here, we take a position on the research directions for which we think the interface between these fields will have the most significant impact and become potential game changers. In our declared agenda for AI in Earth sciences, we aim to inspire researchers, especially the younger generations, to tackle these challenges for a real advance of remote sensing and the geosciences.

Original language	English
Article number	9456877
Pages (from-to)	88-104
Number of pages	17
Journal	IEEE Geoscience and Remote Sensing Magazine
Volume	9
Issue number	2
DOIs	https://doi.org/10.1109/MGRS.2020.3043504
State	Published - Jun 2021

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Funding

Xiao Xiang Zhu is jointly supported by the European Research Council (ERC) under grant ERC-2016-StG-714087, by the Helmholtz Association through the Framework of Helmholtz Artificial Intelligence Cooperation Unit and Helmholtz Excellent Professorship Data Science in Earth Observation\u2014Big Data Fusion for Urban Research, and by the German Federal Ministry of Education and Research in the framework of the international future AI lab AI4EO. Gustau Camps-Valls was partly funded by the ERC under the ERC-SyG-2019 USMILE project (grant agreement 855187). Nathan Jacobs was partly funded by a National Science Foundation CAREER Award (IIS-1553116). Devis Tuia is the corresponding author.

Funders	Funder number
Max Delbrück Center for Molecular Medicine in the Helmholtz Association
Bundesministerium für Bildung und Forschung
Framework of Helmholtz Artificial Intelligence Cooperation Unit and Helmholtz
H2020 European Research Council
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China	647423, 714087, IIS-1553116
Horizon 2020 Framework Programme	855187

ASJC Scopus subject areas

General Computer Science
Instrumentation
General Earth and Planetary Sciences
Electrical and Electronic Engineering

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10.1109/MGRS.2020.3043504

Cite this

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abstract = "In past years, we have witnessed the fields of geosciences and remote sensing and artificial intelligence (AI) become closer. Thanks to the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to help advance the modeling and understanding of the Earth system. Despite such great opportunities, we have also observed a worrisome tendency to remain in disciplinary comfort zones, applying recent advances from AI on well-resolved remote sensing problems. Here, we take a position on the research directions for which we think the interface between these fields will have the most significant impact and become potential game changers. In our declared agenda for AI in Earth sciences, we aim to inspire researchers, especially the younger generations, to tackle these challenges for a real advance of remote sensing and the geosciences.",

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Toward a Collective Agenda on AI for Earth Science Data Analysis

Abstract

Bibliographical note

Funding

ASJC Scopus subject areas

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