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.

翻译：地球观测（EO）是监测陆地与海洋过程、研究动态变化以及感知地球脉搏的重要工具。本文从宏观视角阐述了支撑原始EO数据向可用EO信息转化的核心科学工具与方法。各专门章节重点论述了这些发展的前景及当前面临的挑战。具体涵盖以下方面的影响：（i）计算机视觉；（ii）机器学习；（iii）先进处理与计算技术；（iv）基于知识的人工智能；（v）可解释AI与因果推断；（vi）物理感知模型；（vii）以用户为中心的方法；以及（viii）关于EO中大规模应用机器学习技术所涉及的伦理与社会问题的必要讨论。