Introducing A Novel Compositional Data Analysis Framework for Measuring Land Use Mix in Station Areas
DOI:
https://doi.org/10.25034/ijcua.2026.v10n1-7Keywords:
Land-Use Mix, Isometric Log Ratio Balances, Compositional Data Analysis, Shannon Entropy Index, Station AreasAbstract
This study presents isometric log-ratio (ILR) balances derived from compositional data analysis (CoDA) as a novel framework for measuring the land-use mix, addressing the category insensitivity of the Shannon entropy index (SEI). Six ILR balances were constructed using a theory-driven Sequential Binary Partition of seven residential and commercial functional uses in station buffers within the Osaka Densely Inhabited Districts in Japan. The findings demonstrated that ILR balances successfully clustered three functionally distinct station-area typologies that align with urban outcomes. Comparative analysis of ILR balances and the Shannon entropy index revealed an inverted U-shaped ILR–SEI relationship, demonstrating that ILRs can distinguish compositionally distinct buffers with identical entropy scores. ILR balances further elucidated the sub-component-level interactions, which are masked by the single index of Shannon entropy. Overall, the findings suggest that ILR balances effectively complement the Shannon entropy index by providing category-sensitive directional measurement of functional mix and hierarchical sub-compositional decomposition, offering a more complete and planning-relevant characterization of functional land-use composition around transit stations.
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