preprint وصول مفتوح

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

  • arXiv (Cornell University)
  • Cornell University
Research footprint

At a glance

الاستشهادات
38
المراجع
0
Comments
0
Paper overview

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.

Record transparency

Publication details

DOI
10.48550/arxiv.2305.08413
OpenAlex
W4376653863
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
Last metadata update
المجتمع

Comments

تسجيل الدخول للانضمام إلى النقاش.

  1. لا توجد تعليقات بعد. ابدأ النقاش.