May 2025 Summaries

Organizations in sectors such as climate, energy, and environmental monitoring increasingly collect vast amounts of raster data, including satellite imagery and terrain models, which are often trapped behind complicated legacy systems and manual processes. Despite advancements like Cloud-Optimized GeoTIFFs (COGs) for cloud access, converting raster data into interactive maps remains a complex task involving indexing, metadata creation, and rendering. Felt offers a streamlined solution by connecting data discovery to visualization, transforming cloud storage into a searchable spatial catalog that integrates with existing systems like Spatio-Temporal Asset Catalogs (STACs). Felt automatically indexes raster data, enabling intuitive spatial browsing, powerful metadata filtering, and instant visualization without the need for infrastructure management or custom coding, significantly reducing the time required from weeks or months to mere minutes.

Organizations across various sectors, including climate, energy, infrastructure, and environmental monitoring, are increasingly accumulating large volumes of raster data, such as satellite imagery and terrain models, stored in cloud environments. Despite the availability of modern formats like Cloud-Optimized GeoTIFFs (COGs), which are designed for efficient cloud access, transforming this data into interactive map layers remains a complex process involving metadata cataloging, tile server implementation, and browser rendering. Felt's raster infrastructure simplifies these challenges by connecting data discovery directly to visualization, transforming cloud storage into searchable spatial catalogs, and enabling seamless streaming of COGs to maps. It automates the indexing of raster data, offers intuitive spatial browsing, and facilitates powerful metadata filtering without requiring manual infrastructure management or custom coding. This approach drastically reduces the time and effort needed for data visualization and collaboration, turning what traditionally took weeks or months into a process that can be completed in minutes.