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Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Graph neural networks (GNNs) are a class of neural networks suitable for learning on graph-structured data. Their application to spatial data is a natural extension, however its relatively unclear which message-passing operations, architectural configurations, and graph representation is best suited for classifying changes to objects in electronic navigational charts (ENCs)--geospatial vector datasets used for marine navigation. Maintaining these datasets is a challenge, and categorizing changes to objects in the ENC based on their significance to navigational safety is of particular importanc

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