Understanding the Modifiable Areal Unit Problem and Identifying Appropriate Spatial Units while Studying the Influence of the Built Environment on the Traffic System State

Abstract

Spatially aggregated data are prone to the effects of the modifiable areal unit problem (MAUP), which applies to built environments and traffic data. Although various studies have been carried out to explore the impact of built environment factors on traffic systems, few have considered MAUPs, which may result in statistical inconsistency. The purpose of this study is to assess the effects of MAUPs on statistical variables and geographically weighted regression results when evaluating the influence of the built environment on the traffic system state. Fifty sets of spatial configurations were created using the different aggregation criteria. The variance inflation factor and spatial autocorrelation of the variables, as well as the R2 and root mean squared error of the GWR model, were used to assess the MAUP effect. The results show that the index variation is more dependent on the scale of the spatial unit than on zoning type. In the case study presented, based on the available dataset, the optimal spatial unit size for analyzing the influence of the built environment on Jinan’s traffic system was 900 m × 900 m.

Influence of the built environment on taxi travel demand based on the optimal spatial analysis unit

“…The results showed that the influence of commercial land on taxi commuting demand decreased with an increase in spatial scale. Other studies that considered both the scale and zoning effects of the MAUP have explored the relationship between the built environment and shared bike travel [ 21 ] and the built environment and traffic system state [ 22 ]. Therefore, the MAUP should be fully considered when investigating the relationship between the built environment and taxi travel demand, which will inevitably affect the modeling results.…”