Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward

TL;DR

This review explores how artificial intelligence, including machine learning and explainable AI, is transforming Earth observation by improving data analysis, addressing challenges, and considering ethical issues for sustainable planetary monitoring.

Contribution

It provides a comprehensive overview of AI models, recent trends, and future pathways in Earth observation, highlighting interdisciplinary approaches and societal considerations.

Findings

AI enhances Earth observation data analysis and interpretation.

Emerging AI techniques address current challenges in EO.

Ethical and societal issues are critical in deploying AI for EO.

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.