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How to create a sustainable urban morphology for the development of cities has been an enduring question in urban research. Therefore, quantitatively measuring the current relationship between urban morphology and urban function distribution is the key step before urban planning practice. However, existing studies only examine the relationship at limited scales or with a single unit. To comprehensively understand the relationship between urban morphology and commercial distribution, this study utilized space syntax and point of interest (POI) data (shopping and food service) and took the city of Xi’an, China as a case study. The evaluation of relationships was performed with two measurement units (500 m × 500 m grids and street blocks) at 16 different scales (from R = 800 m to R = n) by engaging three statistical metrics (mean, maximum, and total). Great variations in the relationships between urban morphology and commercial distribution across scales were observed in the study area at both grid level and block level. However, the change trends of the correlation across scales differ substantially when measured by grids and blocks. Generally, the correlations measured by blocks were stronger than those measured by grids, indicating it is desirable to perform such research at the block level. The correlations were stronger at the small scales (R = 800 m to R = 3600 m) when measured with grids, and the stronger correlations were detected at large scales (R = 5 km to R = 35 km) when measured with blocks. The strongest correlations were found at the scale R = 3600 m with grid unit, and the strongest correlations were detected at the scale R = 10 km with blocks. Among the three space syntax variables, urban morphology measured by integration presents stronger correlation with commercial distribution than choice and complex variable for both shopping and food services. This reveals that the centrality of urban space has a greater impact on the locations of commercial establishments than accessibility and comprehensive potential. As for the three statistical metrics, the total is less useful in measuring the impacts of urban morphology on commercial distribution across scales. However, regardless of measurement by grids or by blocks, urban morphology has a stronger impact on the locations of shopping businesses than on food shops. Based on our findings, it is preferable to predict the potential commerce locations by measuring the centrality of the study area at a scale of 10–20 km. Our method can be easily transferred to other urban regions, and the derived results can serve as a valuable reference for government administrators or urban planners in allocating new commerce establishments.
