Quantitative Morphological Analysis and Indicator Identification in Linear Market Towns of the Chengdu Plain of Western Sichuan

The traditional market towns of the Western Sichuan Plain, known as Changzhen, represent a distinctive form of vernacular settlement shaped by the interplay of geographical conditions, migration history, and socio-economic dynamics. In the context of rural revitalisation and integrated urban–rural development, the conservation and renewal of these towns require a deeper understanding of their underlying spatial logic. This study employs a mixed-methods approach combining typo-morphological analysis with spatial measurement and statistical testing to investigate the core morphological indicator that determines plot-type differentiation in linear market towns, using Luodai and Yuantong as two representative cases in the Chengdu Plain. A total of 1113 plots are digitised and measured across four morphological indicators, supplemented by XGBoost classification and SHAP analysis for cross-validation. The findings reveal that plot depth is the core morphological indicator distinguishing the linear type from the enclosed courtyard type, with an effect size substantially larger than that of frontage-to-depth ratio and distance from the street, indicating that plot depth matters more than plot location in determining plot type. The two towns present contrasting patterns of plot-type composition, with frontage enclosed courtyard plots significantly larger than their non-frontage counterparts and no meaningful correlation between plot area and courtyard ratio. This study provides a quantifiable morphological framework for understanding plot-level differentiation in linear market towns and offers practical parameters for conservation and renewal. The findings highlight a specific threshold, with depths below approximately 12 m associated with the linear type and depths above approximately 18 m associated with the enclosed courtyard type, providing a tangible reference for planning decisions in historic districts.