Turning Geospatial Foundation Models into Decisions using CARTO Workflows

CARTO has introduced new capabilities that enable users to perform analytics directly on geospatial foundation model embeddings, facilitating the visualization, clustering, and change detection of spatial data to enhance decision-making processes. Foundation models, trained on diverse datasets such as satellite imagery and online behavior, generate geo-embeddings that encapsulate the context of geographic locations in compact vector forms. These geo-embeddings reveal spatial patterns and relationships, helping organizations to identify trends, optimize infrastructure, and assess risks. Through CARTO Workflows, these complex AI models become accessible to non-experts, allowing integration with existing business, environmental, or demographic datasets. The platform's tools, such as the Geospatial Foundation Models Extension Package, enable users to visualize and analyze embeddings directly in data warehouses like BigQuery, improving scalability and reproducibility without needing specialized machine learning expertise. This advancement in geospatial analysis provides valuable insights across various applications, from urban planning to disaster response, by uncovering patterns previously hidden using traditional methods.