The development of methods for dividing a region into sub-regions that are spatially contiguous and as homogeneous as possible

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This study first proposed an isopleth-based regionalization method and implemented the method and other regionalization methods in a computer environment. We then applied several regionalization methods including the isopleth-based method to a numerous number of datasets and make comparisons between the regionalization methods in terms of the homogeneity of sub-regions. We revealed that the isopleth-based method on average outperforms other methods when the number of spatial units is very small. We also revealed that the isopleth-based method may underperform other methods when there is strong spatial autocorrelation in a dataset and also when the correlation between attribute variables is very weak. Although the isopleth-based method may underperform under certain conditions, we however demonstrated that the isopleth-based method does not underperform if the number of spatial units is large enough. Overall, it appears that the performance of the isopleth-based regionalization method is satisfactory. However, the algorithm for executing the method should be developed further. We hope to tackle the technical issue in the future.