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Artificial intelligence to advance Earth observation: a perspective

Authors :
Tuia, Devis
Schindler, Konrad
Demir, Begüm
Camps-Valls, Gustau
Zhu, Xiao Xiang
Kochupillai, Mrinalini
Džeroski, Sašo
van Rijn, Jan N.
Hoos, Holger H.
Del Frate, Fabio
Datcu, Mihai
Quiané-Ruiz, Jorge-Arnulfo
Markl, Volker
Saux, Bertrand Le
Schneider, Rochelle
Publication Year :
2023

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2305.08413
Document Type :
Working Paper