UNIGEOCLIP creates a unified embedding for aerial imagery, street views, elevation, text, and coordinates via all-to-all contrastive alignment plus a scaled lat-long encoder, outperforming single-modality and coordinate baselines on geospatial tasks.
Community search signatures as foundation features for human-centered geospatial modeling
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A GNN-based foundation model on aggregated US geospatial data produces embeddings achieving SOTA on all 27 interpolation tasks and 25/27 extrapolation/super-resolution tasks across health, socioeconomic and environmental domains, plus improved forecasting when combined with TimesFM.
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UNIGEOCLIP: Unified Geospatial Contrastive Learning
UNIGEOCLIP creates a unified embedding for aerial imagery, street views, elevation, text, and coordinates via all-to-all contrastive alignment plus a scaled lat-long encoder, outperforming single-modality and coordinate baselines on geospatial tasks.
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General Geospatial Inference with a Population Dynamics Foundation Model
A GNN-based foundation model on aggregated US geospatial data produces embeddings achieving SOTA on all 27 interpolation tasks and 25/27 extrapolation/super-resolution tasks across health, socioeconomic and environmental domains, plus improved forecasting when combined with TimesFM.