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Artificial intelligence to advance Earth observation: a perspective

15 May 2023
D. Tuia
Konrad Schindler
Begum Demir
Gustau Camps-Valls
Xiao Xiang Zhu
M. Kochupillai
S. Džeroski
Jan N. van Rijn
Holger H. Hoos
Fabio Del Frate
Mihai Datcu
Jorge-Arnulfo Quiané-Ruiz
Volker Markl
Bertrand Le Saux
Rochelle Schneider
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Abstract

Earth observation (EO) is a prime instrument for monitoring land and ocean processes, studying the dynamics at work, and taking the pulse of our planet. This article gives a bird's eye view of the essential scientific tools and approaches informing and supporting the transition from raw EO data to usable EO-based information. The promises, as well as the current challenges of these developments, are highlighted under dedicated sections. Specifically, we cover the impact of (i) Computer vision; (ii) Machine learning; (iii) Advanced processing and computing; (iv) Knowledge-based AI; (v) Explainable AI and causal inference; (vi) Physics-aware models; (vii) User-centric approaches; and (viii) the much-needed discussion of ethical and societal issues related to the massive use of ML technologies in EO.

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