AI raster analysis is here: zonal stats, elevation profiles and more

Felt has introduced integrated raster analysis capabilities to its collaborative GIS platform, enabling users to perform workflows previously requiring separate infrastructure and specialized tools. Available through the Felt AI Assistant and MCP, the new functions include zonal statistics, raster-band analysis, spatial filtering and clipping, elevation and route profiles, and enrichment of vector features with raster-derived values. Users can sample pixel values for points, lines, and polygons; create dashboard components such as histograms and filters from raster bands or derived indices including NDVI; and interactively update results when boundaries, routes, or selected ranges change. Felt positions its AI tools as a way to automate tasks such as locating relevant raster data, combining it with vector data, and ranking candidate areas, illustrated by a renewable-energy siting example involving wind conditions and existing turbines.

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