mlsanityData to 7 Oct 2026

Responsible AI for Earth Observation

arXiv 2405.20868 ↗First posted 31 May 2024cs.CV cs.CYcited by 4

Not on the map. Why?

Abstract (arXiv)

The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO platforms, holds great promise in addressing global challenges such as environmental monitoring, disaster response and climate change analysis. However, the rapid integration of AI necessitates a careful examination of the responsible dimensions inherent in its application within these domains. In this paper, we represent a pioneering effort to systematically define the intersection of AI and EO, with a central focus on responsible AI practices. Specifically, we identify several critical components guiding this exploration from both academia and industry perspectives within the EO field: AI and EO for social good, mitigating unfair biases, AI security in EO, geo-privacy and privacy-preserving measures, as well as maintaining scientific excellence, open data, and guiding AI usage based on ethical principles. Furthermore, the paper explores potential opportunities and emerging trends, providing valuable insights for future research endeavors.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 32 of its 156 references that are in the map. First posted on arXiv 31 May 2024.

Builds on

32 of 156 references.

References · 32

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20 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.

  1. 2024MineNetCD: A Benchmark for Global Mining Change Detection on Remote Sensing Imagerycited by 7
  2. 2024ChangeMinds: Multi-task Framework for Detecting and Describing Changes in Remote Sensingcited by 7
  3. 2025HyperPointFormer: Multimodal Fusion in 3D Space with Dual-Branch Cross-Attention Transformerscited by 1
  4. 2026Survey on Disaster Management Datasets for Remote Sensing Based Emergency Applicationscited by 0