Conference paper Open Access

A Supervised Heuristic for a Balanced Approach to Regionalization

Hoffman, Tyler D.; Oshan, Taylor

Regionalization refers to the design of areal zones by spatially aggregating smaller units into larger clusters. Algorithms to conduct regionalization typically require the desired number of clusters to be specified a priori, though a reasonable number is not always clear. Therefore, a heuristic is proposed to endogenously determine the number of clusters in a supervised setting (i.e., model-driven) by balancing the fit of a spatial model and the average area of clusters used as input. The heuristic is applied in a spatial interaction modeling context and a workflow is presented for integrating regionalization algorithms into larger spatial analysis frameworks.

Files (365.8 kB)
Name Size
365.8 kB Download
All versions This version
Views 9292
Downloads 6767
Data volume 24.5 MB24.5 MB
Unique views 8585
Unique downloads 6262


Cite as