Spatial H3 Hub
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Discover Datasets & Insight-Ready Projects
Instantly access H3-indexed datasets via our FSQ Spatial Agent and Iceberg catalog, or leverage plug-and-play projects to generate complex analyses & visualizations in moments in FSQ Spatial Desktop.
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\ \ Dataset\ \ MODIS Land Cover 500m 2024 \ \ A global map of land cover - forests, croplands, urban areas, water, etc. - at roughly 500 m resolution, observed in 2023 and released in 2024. Useful for ecology, agriculture, climate, and land-change studies at broad scales.\ \ NASA's MODIS Land Cover MCD12Q1 Version 6.1, derived from MODIS Terra and Aqua reflectance data. Includes five land-cover classification schemes (IGBP, UMD, LAI, BGC, PFT) and Land Cover Land Use (LCLU) layers based on the FAO LCCS. Values are aggregated to H3 cells with the mode and pixel count for each band. Legend for each band is in the user guide: https://lpdaac.usgs.gov/documents/1409/MCD12\_User\_Guide\_V61.pdf](https://spatial-h3-hub.foursquare.com/dataset/MODIS%20Land%20Cover%20500m%202024/details)
\ \ Project\ \ NYC Transit Homebuyer \ \ This analysis provides a data-driven foundation for your home search, identifying areas that balance affordability with excellent public transit access to Midtown Manhattan. The green areas on the map represent your best opportunities as a budget-conscious, first-time homebuyer prioritizing commute convenience!](https://spatial-h3-hub.foursquare.com/project/53b7fda7-b298-44e6-9deb-ef0eb6f68b66/details)
\ \ Dataset\ \ Urban Access To Public Transportation \ \ An estimate, for thousands of cities worldwide, of what share of residents live within convenient walking distance of public transport. Useful for tracking progress on UN Sustainable Development Goal 11 (make cities safe, resilient, and sustainable) and for comparing transit accessibility across urban areas.\ \ The SDG Indicator 11.2.1: Urban Access to Public Transport, 2023 Release (part of the SDGI collection). Computed as the share of WorldPop gridded population within 0.5 km walking distance to a low-capacity OpenStreetMap (OSM) public transport point or 1 km walking distance to a high-capacity OSM public transport point. Cities are delineated using the European Commission Joint Research Centre (JRC) Urban Center Database (UCDB); coverage is 5,749 urban centers across 178 countries.](https://spatial-h3-hub.foursquare.com/dataset/Urban%20Access%20To%20Public%20Transportation/details)
\ \ Dataset\ \ Critical Mineral Distribution Points \ \ A global map of mines, deposits, and mining districts that produce or contain minerals the U.S. has identified as critical to its economy and security. Useful for supply-chain analysis, geopolitical and economic research, and work on strategic resources.\ \ From the U.S. Geological Survey (USGS), as of 2017, covering 22 critical minerals (e.g., antimony, lithium, rare-earth elements). Each point includes location, deposit name, type, and key mineral information. Part of USGS Scientific Investigations Report 2017-5118.](https://spatial-h3-hub.foursquare.com/dataset/Critical%20Mineral%20Distribution%20Points/details)
\ \ Project\ \ Chandler Urban Planning \ \ Comprehensive multi-layered spatial analysis of Chandler, Arizona using H3 Hub datasets covering 202 H3 cells (resolution 8) across the city. The analysis integrated 5 major spatial layers: housing, population/demographics, infrastructure, environmental hazards, and air quality to provide actionable recommendations for urban planning.](https://spatial-h3-hub.foursquare.com/project/388f5020-3286-425f-a685-44220576b787/details)
\ \ Dataset\ \ Chelsa Climate Projections SSP370 \ \ Projected future climate for the world's land surface under a medium-high greenhouse-gas emissions pathway, alongside a recent historical baseline. The dataset captures five core climate variables — annual average temperature, annual precipitation, warmest-month and coldest-month temperatures, and how much precipitation varies across the year — at three time slices, so it can be used to compare current conditions with mid- and late-century projections.\ \ Derived from the CHELSA (Climatologies at High resolution for the Earth's Land Surface Areas) bioclimatic variables for a 1981-2010 baseline and 2011-2040 and 2041-2070 projections under SSP3-7.0 (a medium-high emissions scenario characterized by regional rivalry and slow progress toward sustainability). The five variables correspond to CHELSA bio1 (annual mean temperature), bio12 (annual precipitation), bio5 (max temperature of warmest month), bio6 (min temperature of coldest month), and bio15 (precipitation seasonality). Temperature values are scaled by 10 (e.g., 150 = 15.0 °C). Projections are based on MPI-ESM1-2-HR climate model simulations.](https://spatial-h3-hub.foursquare.com/dataset/Chelsa%20Climate%20Projections%20SSP370/details)
\ \ Project\ \ California Wildfire Risk \ \ A comprehensive wildfire risk analysis for California's populated areas using H3 Hub data at resolution 8 (hexagons ~0.74 km² each).](https://spatial-h3-hub.foursquare.com/project/fd51c9de-c531-4ab7-885d-cc8539864ff5/details)
\ \ Vector\ \ Tribal Leaders Directory\ \ Owner: Bureau of Indian Affairs\ \ Locations\ \ United States](https://spatial-h3-hub.foursquare.com/dataset/Tribal%20Leaders%20Directory/details)
\ \ Vector\ \ OS Places\ \ Owner: Foursquare\ \ Locations\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/OS%20Places/details)
\ \ Vector\ \ Crashes In DC\ \ Owner: Metropolitan Police Department of the DC\ \ Locations\ \ United States](https://spatial-h3-hub.foursquare.com/dataset/Crashes%20In%20DC/details)
\ \ New\ \ Raster\ \ Crop Type Layer 2023\ \ Owner: European Environment Agency\ \ Environment\ \ European Union](https://spatial-h3-hub.foursquare.com/dataset/Crop%20Type%20Layer%202023/details)
\ \ New\ \ Raster\ \ ERA5 Global Weather Weekly\ \ Owner: European Centre for Medium-Range Weather Forecasts\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/ERA5%20Global%20Weather%20Weekly/details)
\ \ Vector\ \ GridMET Weekly Weather\ \ Owner: Climatology Lab\ \ Environment\ \ United States](https://spatial-h3-hub.foursquare.com/dataset/GridMET%20Weekly%20Weather/details)
\ \ Raster\ \ FIRMS Weekly\ \ Owner: NASA\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/FIRMS%20Weekly/details)
\ \ Raster\ \ Surface PM 25 Annual 2023\ \ Owner: Atmospheric Composition Analysis Group\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/Surface%20PM%2025%20Annual%202023/details)
\ \ Raster\ \ Soilgrids Select Variables\ \ Owner: International Soil Reference and Information Centre\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/Soilgrids%20Select%20Variables/details)
\ \ Raster\ \ Climate Extremes RCP85 25yr\ \ Owner: Copernicus Climate Change Service \ \ Environment\ \ Europe](https://spatial-h3-hub.foursquare.com/dataset/Climate%20Extremes%20RCP85%2025yr/details)
\ \ Vector\ \ Natura 2000\ \ Owner: European Environment Agency\ \ Environment\ \ European Union](https://spatial-h3-hub.foursquare.com/dataset/Natura%202000/details)
\ \ Raster\ \ Global Forest Canopy Height\ \ Owner: Global Land Analysis and Discovery (GLAD) \ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/Global%20Forest%20Canopy%20Height/details)
\ \ Raster\ \ MODIS Land Cover 500m 2024\ \ Owner: NASA\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/MODIS%20Land%20Cover%20500m%202024/details)
\ \ Raster\ \ FIRMS Weekly\ \ Owner: NASA\ \ Environment\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/FIRMS%20Weekly/details)
\ \ Vector\ \ Commuting Zones\ \ Owner: Data For Good at Meta\ \ Demography\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/Commuting%20Zones/details)
\ \ Vector\ \ OS Places\ \ Owner: Foursquare\ \ Locations\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/OS%20Places/details)
\ \ Raster\ \ Accessibility To Cities\ \ Owner: Google\ \ Reachability\ \ Global](https://spatial-h3-hub.foursquare.com/dataset/Accessibility%20To%20Cities/details)
Introducing Projects...
Explore pre-made projects with H3-indexed spatial analyses and visualizations in FSQ Spatial Desktop. Easily access full FSQ Spatial Agent chats to see how projects were generated, ask follow-up questions and inspire your own analyses. Download the app today and import projects to get started.
Learn more about FSQ Spatial Desktop
\ \ Los Angeles Banking insights](https://spatial-h3-hub.foursquare.com/project/cbef90bb-86f4-4d1d-9b43-ba8b6c46f808/details)
\ \ European Climate Extremes](https://spatial-h3-hub.foursquare.com/project/3ec1a463-72f1-4129-bbb9-ecce1fd14f80/details)
\ \ Animated Flight Map](https://spatial-h3-hub.foursquare.com/project/aa590fb1-9172-4f5a-b16c-0123fb5fb2fe/details)
\ \ Italian Wine Regions](https://spatial-h3-hub.foursquare.com/project/a4fb2f75-891b-4f02-95af-e9f7aeaf7d2c/details)
\ \ Chandler Urban Planning](https://spatial-h3-hub.foursquare.com/project/388f5020-3286-425f-a685-44220576b787/details)
\ \ Agricultural Opportunity](https://spatial-h3-hub.foursquare.com/project/cfff4929-6efd-4dac-87ef-e914f0c73b89/details)
\ \ California Wildfire Risk](https://spatial-h3-hub.foursquare.com/project/fd51c9de-c531-4ab7-885d-cc8539864ff5/details)
\ \ NYC Transit Homebuyer](https://spatial-h3-hub.foursquare.com/project/53b7fda7-b298-44e6-9deb-ef0eb6f68b66/details)
\ \ European Green Space](https://spatial-h3-hub.foursquare.com/project/62e72789-b7fb-4016-b5a8-0686074aedc3/details)
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