Oct 10, 2025
Understand how Population Explorer combines global population, demographic, income, and POI datasets for precise spatial analysis.
Overview
Every map, buffer, and population estimate in Population Explorer (PopEx) is powered by a carefully curated combination of demographic, economic, and geospatial data sources. Whether you’re planning franchise territories, analyzing cell coverage, supporting humanitarian logistics, or conducting retail site selection, these datasets form the foundation of every decision.
PopEx blends population grids from global providers such as LandScan (Oak Ridge National Laboratory) and WorldPop (University of Southampton) with administrative boundaries, income and demographic layers, and points of interest (POIs) from trusted open and commercial sources, including Google Places and OpenStreetMap. Each dataset is standardized to a common coordinate system, normalized for projection accuracy, and cached on PopEx servers for near-instant access.
Our platform’s intelligence layer ensures that every population total, density, or demographic summary you see reflects a synthesis of the most current and accurate data available. This means that when you draw a buffer, import a boundary, or generate a drive-time isochrone, PopEx instantly intersects that shape with the underlying population grid and returns precise totals — weighted where necessary to handle partial overlaps or mixed land-use zones.
This same approach scales across industries: a telecom planner uses population coverage grids to measure service demand; a retailer compares income levels near competing POIs; a humanitarian analyst estimates people within a floodplain. PopEx abstracts the complexity of GIS data integration into a few intuitive steps, so your focus stays on analysis, not preprocessing.
How to Explore the Data Layers
1. Open the Layers Panel
Click Layers → Settings from the map viewing pane. You’ll see available population datasets organized by year.
2. Toggle Population Grids
Activate heatmaps to view population counts as shaded rasters.
3. Review Demographic and Income Layers
Review demographic overlays after creating a shape in the map viewing pane (age, gender) or income bands to evaluate purchasing power and socioeconomic diversity. These are especially useful in retail site selection and sales territory analysis.
4. Add Points of Interest (POIs)
Search Google POIs to reveal nearby businesses, amenities, and competitors. In urban areas, this helps quantify commercial density and understand the competitive landscape.
