Feature Description

Generates Thiessen polygons based on given point datasets. Thiessen polygons can be used for qualitative analysis, statistical analysis, proximity analysis, etc. For example:

• Use properties of discrete points to describe polygon regions
• Calculate polygon area data using discrete point data
• Determine adjacent discrete points through polygon edges (n-sided polygon indicates n neighboring points)
• Directly identify nearest discrete points without distance calculation when data points fall within polygons

Definition

Thiessen polygons, proposed by Dutch climatologist A.H.Thiessen for calculating average rainfall, are created by:

1. Connecting adjacent weather stations into triangles
2. Drawing perpendicular bisectors of triangle edges
3. Forming polygonal areas bounded by these bisectors

Each polygon contains one unique station, representing regional rainfall intensity. Also known as Voronoi diagrams, Thiessen polygons exhibit three key characteristics:

1. Each polygon contains exactly one discrete point
2. All locations within a polygon are closest to its contained point
3. Points on polygon edges are equidistant to two neighboring discrete points

Applications

Thiessen polygons enable spatial partitioning and nearest-point allocation, serving as alternatives to interpolation for generalizing sample measurements. Typical use cases include:

• Generalizing climate measurements from stations to surrounding areas
• Creating service areas for retail stores
• Conducting proximity analysis for facility planning

Parameter Description

Output

Use Case

This example constructs Thiessen polygons using nationwide meteorological station data, transferring point attributes to polygonal regions. The resulting polygons represent average rainfall areas for each station. A segmented thematic map created from this data enables analysis of regional rainfall distribution patterns, as shown in the national rainfall distribution map below: