mlsanityData to 14 Oct 2026

Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation

arXiv 2411.03223 ↗First posted 5 Nov 2024cs.LG cs.AI cs.CVcited by 3

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Abstract (arXiv)

Earth Observation (EO) data analysis has been significantly revolutionized by deep learning (DL), with applications typically limited to grid-like data structures. Graph Neural Networks (GNNs) emerge as an important innovation, propelling DL into the non-Euclidean domain. Naturally, GNNs can effectively tackle the challenges posed by diverse modalities, multiple sensors, and the heterogeneous nature of EO data. To introduce GNNs in the related domains, our review begins by offering fundamental knowledge on GNNs. Then, we summarize the generic problems in EO, to which GNNs can offer potential solutions. Following this, we explore a broad spectrum of GNNs' applications to scientific problems in Earth systems, covering areas such as weather and climate analysis, disaster management, air quality monitoring, agriculture, land cover classification, hydrological process modeling, and urban modeling. The rationale behind adopting GNNs in these fields is explained, alongside methodologies for organizing graphs and designing favorable architectures for various tasks. Furthermore, we highlight methodological challenges of implementing GNNs in these domains and possible solutions that could guide future research. While acknowledging that GNNs are not a universal solution, we conclude the paper by comparing them with other popular architectures like transformers and analyzing their potential synergies.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 96 of its 213 references that are in the map. First posted on arXiv 5 Nov 2024.

Builds on

96 of 213 references.

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Cited by year (2026 to 14 Oct)

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

3 papers.

  1. 2026Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODEcited by 1
  2. 2025i-WiViG: Interpretable Window Vision GNNcited by 0
  3. 2025On the use of Graphs for Satellite Image Time Seriescited by 0