arXiv Machine Learning September 10, 2026 By Yu Li, Guilherme N. DeSouza, Praveen Rao, Chi-Ren Shyu

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

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The paper introduces the Geo-Context Guided Visual Transformer, a model that augments remote sensing image analysis with geospatial embeddings and an asymmetric attention module. By converting heterogeneous geospatial variables into patch-aligned representations and assigning geospatial roles to attention heads, the approach improves disease prevalence prediction over existing vision-language and graph-based baselines. Ablation and visualization studies demonstrate its effectiveness and interpretability for health-related remote sensing tasks, especially when comprehensive geospatial data are scarce.

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