Voronoi Diagram Generator
Upload a point dataset (GeoJSON, KML, or GPX) and generate Voronoi polygons. Download as GeoJSON or KML.
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GeoJSON, KML, GPX — point features only
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What is a Voronoi diagram?
A Voronoi diagram (also called a Thiessen polygon diagram) partitions a plane into regions based on proximity to a set of seed points. Each region contains exactly the area that is closer to its seed point than to any other seed. The boundaries between regions are equidistant from the two nearest seeds.
Voronoi diagrams are a fundamental structure in computational geometry and appear in many natural phenomena — the pattern of cells in a leaf, the distribution of craters on a surface, and the territories of competing species all approximate Voronoi partitions.
Common use cases
Nearest-facility service areas
Determine which hospital, fire station, or store is closest to any given location by assigning each area to its nearest facility.
Telco and WiFi coverage planning
Model approximate coverage zones for cell towers or access points by partitioning the area around each transmitter.
Spatial partitioning
Divide a study area into non-overlapping zones for spatial sampling, survey design, or administrative allocation.
Point pattern analysis
Analyse the spacing and clustering of point data by examining the size and shape of Voronoi cells.
Frequently asked questions
What input data does the Voronoi generator need?
The tool needs a point dataset — upload a GeoJSON, KML, or GPX file containing point features. Each point becomes a seed for one Voronoi polygon. Line and polygon features are ignored.
What is the difference between a Voronoi diagram and a Delaunay triangulation?
They are duals of each other. The Delaunay triangulation connects seed points with triangles; the Voronoi diagram draws perpendicular bisectors between those triangles to form regions. The TIN Generator on this site produces Delaunay triangulations.
How are edge polygons handled at the boundary?
The output is clipped to the bounding box of the input points (with a small buffer). Edge polygons that would extend to infinity are clipped at this boundary, so the output is always a finite set of polygons.
Can I use Voronoi polygons to determine service areas?
Yes — Voronoi polygons are a common approximation for service areas. Each polygon contains all locations closer to its seed point than to any other seed, making it suitable for nearest-facility analysis when road-network routing is not required.