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GeoAI as Collaborative Effort

Interview with Devis Tuia

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Notes

  1. https://landsat.gsfc.nasa.gov.

  2. https://www.geo.uzh.ch/en/units/gco.html.

  3. https://www.epfl.ch/schools/enac/research/environmental-engineering-institute-iie/alpole-en/.

  4. https://trsc.org/en/.

  5. https://eceo.epfl.ch.

  6. https://www.dair-institute.org/about.

  7. https://ebird.org/home.

  8. https://www.belongielab.org.

  9. Example attributed to Ross Purves.

References

  1. Tollenaar V, Zekollari H, Tuia D, Kellenberger B, Rußwurm M, Lhermitte S, et al (2022) What determines the location of Antarctic blue ice areas? A deep learning approach. In: EGU General Assembly 2022. EGU22-1294. Vienna, Austria; Available from: https://doi.org/10.5194/egusphere-egu22-1294.

  2. Persello C, Wegner JD, Hänsch R, Tuia D, Ghamisi P, Koeva M et al (2022) Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities. IEEE Geosci Remote Sens Mag 10(2):172–200. https://doi.org/10.1109/MGRS.2021.3136100

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  3. Tuia D, Kellenberger B, Beery S, Costelloe BR, Zuffi S, Risse B et al (2022) Perspectives in machine learning for wildlife conservation. Nat Commun 13(1):792. https://doi.org/10.1038/s41467-022-27980-y

    Article  Google Scholar 

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Correspondence to Kai-Florian Richter.

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Richter, KF., Scheider, S. & Tuia, D. GeoAI as Collaborative Effort. Künstl Intell 37, 99–105 (2023). https://doi.org/10.1007/s13218-022-00791-5

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