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Collaboration between artificial intelligence and Earth science communities for mutual benefit

Artificial intelligence is rapidly being integrated into Earth science, but how Earth science may benefit artificial intelligence has been overlooked. We call for mutual balancing between the two disciplines and improving cross-disciplinary collaboration.

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Fig. 1: Collaboration between AI and ES towards AIXES.

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Acknowledgements

M.C. acknowledges funding by the National Natural Science Foundation of China for Distinguished Young Scholars under grant agreement no. 42325107. G.L. acknowledges funding by the National Natural Science Foundation of China under grant agreement no. 41930648 and the International Research Center of Big Data for Sustainable Development Goals under grant agreement no. CBAS2022GSP08. N.B. acknowledges funding from the Volkswagen Foundation and the European Union’s Horizon Europe research and innovation programme under grant agreement no. 101137601 (ClimTip). G.C-V. thanks the support of the European Research Council (ERC) under the ERC Synergy Grant USMILE (grant agreement no. 855187) and the Horizon Europe project ELIAS (grant agreement no. 101120237).

Author information

Author notes

  1. These authors contributed equally: Min Chen, Zhen Qian.

Authors and Affiliations

  1. Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing, Jiangsu, China

    Min Chen, Zhen Qian, Josef Strobl, A-Xing Zhu, Linwang Yuan & Guonian Lü

  2. International Research Center of Big Data for Sustainable Development Goals, Beijing, China

    Min Chen

  3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, China

    Min Chen, Linwang Yuan & Guonian Lü

  4. Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany

    Zhen Qian, Niklas Boers & Philipp Hess

  5. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    Zhen Qian, Niklas Boers & Philipp Hess

  6. Department of Mathematics and Global Systems Institute, University of Exeter, Exeter, UK

    Niklas Boers

  7. Mercator Research Institute on Global Commons and Climate Change, Berlin, Germany

    Felix Creutzig & Zhixin Zhang

  8. Sustainability Economics of Human Settlements, Technical University Berlin, Berlin, Germany

    Felix Creutzig & Zhixin Zhang

  9. Science Policy Research Unit (SPRU), University of Sussex Business School, East Sussex, UK

    Felix Creutzig

  10. Image Processing Laboratory (IPL), Universitat de València, València, Spain

    Gustau Camps-Valls

  11. Integrated Research on Energy, Environment and Society, Energy and Sustainability Research Institute Groningen, University of Groningen, Groningen, The Netherlands

    Klaus Hubacek

  12. Naval Academy Research Institute, Lanvéoc, France

    Christophe Claramunt

  13. Spatial Sciences Institute, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA

    John P. Wilson

  14. Departments of Civil & Environmental Engineering and Computer Science, Viterbi School of Engineering, and School of Architecture, University of Southern California, Los Angeles, CA, USA

    John P. Wilson

  15. National Research Council of Italy, Institute of Atmospheric Pollution Research – Unit of Florence, Roma, Italy

    Stefano Nativi

  16. Fenner School of Environment and Society, Australian National University, Canberra, Australia

    Anthony J. Jakeman

  17. EarthByte Group, School of Geosciences, University of Sydney, Sydney, New South Wales, Australia

    R. Dietmar Müller

  18. Centre for Advanced Spatial Analysis, University College London, London, UK

    Michael Batty

  19. The Alan Turing Institute, The British Library, London, UK

    Michael Batty

  20. State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing, China

    Chenghu Zhou

  21. State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    Fahu Chen

  22. Faculty of Geographical Science, Beijing Normal University, Beijing, China

    Qiao Wang

  23. Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University, Beijing, China

    Fan Zhang

  24. School of Human Evolution and Social Change and School of Complex Adaptive Systems, Arizona State University, Tempe, AZ, USA

    C. Michael Barton

  25. Department of Geoinformatics – Z_GIS, University of Salzburg, Salzburg, Austria

    Josef Strobl

  26. School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, China

    Michael Meadows

  27. Department of Environmental & Geographical Science, University of Cape Town, Rondebosch, South Africa

    Michael Meadows

  28. Senseable City Lab, Massachusetts Institute of Technology, Cambridge, MA, USA

    Carlo Ratti

  29. ABC Department, Politecnico di Milano, Milan, Italy

    Carlo Ratti

  30. Data Science in Earth Observation, School of Engineering and Design, Technical University of Munich, Munich, Germany

    Qingsong Xu

  31. Department of Tourism, School of Humanities, Southeast University, Nanjing, Jiangsu, China

    Qiushi Gu

  32. Department of Geography, University of Wisconsin–Madison, Madison, WI, USA

    A-Xing Zhu

  33. Key Laboratory of Poyang Lake Wetland and Watershed Research (Ministry of Education of PRC), Jiangxi Normal University, Nanchang, Jiangxi, China

    Hui Lin

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  1. Min Chen
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Min Chen or Guonian Lü.

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Cite this article

Chen, M., Qian, Z., Boers, N. et al. Collaboration between artificial intelligence and Earth science communities for mutual benefit.
Nat. Geosci. 17, 949–952 (2024). https://doi.org/10.1038/s41561-024-01550-x

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  • Published: 09 October 2024

  • Issue Date: October 2024

  • DOI: https://doi.org/10.1038/s41561-024-01550-x

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