Spatial clustering is a fundamental method of geographical analysis that detects patterns from location data.

Spatial clustering consists of labeling the observations of a dataset, so that observations with the same label share common characteristics spatially. Clustering is widely used to provide insights into the geographic structure of complex spatial data. LISA Hotspot is a spatial clustering algorithm that fully considers spatial dependence.

Regionalization is a special kind of clustering to group observations, which are similar not only in their statistical attributes, but also in their spatial location. Observations are grouped so that each spatial cluster, or region, is spatially-coherent as well as data-coherent. DBSCAN with Regionalization and Agglomerative with Regionalization are two such clustering algorithms.