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Site selection decisions involve evaluating hundreds of spatial variables across thousands of candidate locations. With Wherobots, you can generate drive-time catchments, join candidate sites with demographic and POI data, and score them by proximity and clustering.

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Examples

Trade Area Analysis

Generate isochrones and trade areas around candidate sites to understand drive-time catchments, population coverage, and competitive overlap using Spatial SQL.

Demographic & Market Scoring

Join candidate locations with census data, such as the US Census American Community Survey estimates in the Data Hub, and your own market data to score sites.

Competitor Proximity & Saturation

Measure how saturated each candidate market is by finding the k nearest competing locations for every site in a single distributed join.

Pedestrian Access

Detect sidewalks and crosswalks around candidate locations from aerial imagery with RasterFlow.

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Key Capabilities

Generate drive-time and walk-time isochrones for every candidate location in one query to see the area that can reach each site within a travel time.

Making drive time isochrones

Build travel-time polygons for every candidate location at once.
Use DBSCAN clustering to identify natural groupings of demand signals, competitor locations, or customer addresses to inform where gaps and opportunities exist.

DBSCAN clustering

Find natural groupings in demand and competitor locations.
Apply Getis-Ord Gi* statistics to identify statistically significant spatial concentrations of demand, revenue, or other performance metrics across geographies.

Hotspot detection

Separate real concentrations from noise with Getis-Ord Gi*.
Find the k nearest competitors, transit stops, or distribution centers for every candidate site in one distributed join, and use the resulting distances as scoring inputs.

k-Nearest Neighbor joins

Score every candidate by distance to its nearest competitors.
Calculate aggregate statistics within trade areas, zip codes, or custom polygons. Summarize population density, income levels, land cover mix, and more for each zone.

Zonal statistics

Summarize raster values inside your own trade area boundaries.

Get started with Wherobots

Try Wherobots with your own geospatial data in minutes.