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World Signal is a product that monitors real-world systems like earthquakes, wildfires, internet connectivity, and aviation to detect unusual activity across the planet, allowing users to explore anomalies and compare them with historical data.
A systematic evaluation of the COTQ provincial land cover product for Quebec, comparing it with ESA WorldCover, ESRI LandCover, and Google DynamicWorld through structural consistency, spectral separability, and relative positioning analyses.
AARAB, a multi-agent AI system, completed a geospatial analysis of renewable energy potential in East Africa in under 4 minutes.
MABLE combines masked reconstruction with cosine-similarity losses to learn node and graph embeddings from large heterogeneous graphs, demonstrated on geospatial mineral-exploration data. It unifies masked autoencoding and metric learning in a self-supervised framework without requiring labeled data.