Spatial clustering is a research area within the field of spatial analysis and data mining that focuses on identifying groups or clusters of spatially related data points. This could involve identifying clusters of similar land use patterns, crime hotspots, or disease outbreak locations. Spatial clustering techniques aim to highlight patterns and relationships within spatial data sets to aid in decision-making and understanding of spatial phenomena. Some common methods used in spatial clustering include K-means clustering, DBSCAN, hierarchical clustering, and spectral clustering.