Post by Foursquare

New in FSQ Spatial: ⏳ temporal datasets in H3 Hub and 🎞️ time series animation in Spatial Desktop! Standard weather rasters make for pretty animations, but they’re a nightmare for data pipelines. Here’s our fix:   We took massive, continuous global data feeds and indexed them directly to the H3 grid to make every “pixel” over time a discrete, queryable row. Now, we can execute multi-domain, temporal joins in seconds! Here’s what this looks like in practice ⬇️ In the analysis below of the 2026 Georgia flash drought, see how you can instantly go from smooth rasters to discrete, filterable, and joinable data points. →  First we mapped out daily max temperatures and precipitation across Georgia to create what looks like your typical climate dashboard (smooth, raster-like gradients of record heat and zero rain sweeping across the state). → We then overlaid the weekly US Drought Monitor on top of the USDA Cropland Data Layer to highlight critical cotton and peanut fields. Right at the peak of the drought, we freeze time and zoom in. (Tip: use temporal filters to see how datasets change over time.) → See how the map shatters into hexagons? Every hexagon isn’t a pixel, it’s a discrete data point at H3 resolution 8. And since the disparate datasets share the exact same spatial grid, now we can just run a standard join to calculate ground-truth agricultural risk. Try it out! Explore temporal datasets and run your own analyses in FSQ Spatial Desktop - link in comments to get the latest version 👇