Klusterkartor

Klusterkartor are maps that display clusters identified in data or space, typically produced with geographic information systems (GIS) or data-visualization tools. In a cluster map, geographic units such as regions, municipalities, or grid cells are colored by cluster membership, revealing spatial patterns of similarity or difference. The term is widely used in Swedish contexts to describe maps that summarize results from cluster analysis or spatial statistics.

Uses and examples: They are used in fields such as epidemiology to show disease clusters, urban planning to delineate homogeneous regions, marketing to segment markets, and criminology to highlight hotspots. They can be based on non-spatial attributes (attribute clustering) or on spatial proximity (spatial clustering).

Methods: Clustering can be performed with non-spatial algorithms such as k-means or hierarchical clustering on attribute data, or with spatial methods such as DBSCAN, spatially-constrained clustering, or techniques like Getis-Ord Gi* and Moran's I to identify hot spots. The resulting cluster labels are then mapped to colors. Clusters may be defined for administrative units, grid cells, or custom polygons, and may be static or time-enabled.

Design and interpretation: Effective cluster maps use clear color palettes, legible legends, and an appropriate number of clusters. They require careful interpretation, since results depend on data quality, scale, and the chosen method. They do not imply causation and may be affected by the modifiable areal unit problem (MAUP).

See also: cluster analysis, spatial analysis, GIS, hot spot analysis, choropleth map.