Development of a Differential Spatial Economic Modeling Method for Improved Land Use and Multimodal Transportation Planning

Muhammad Safdar (), Ming Zhong, Linfeng Li, Asif Raza and John Douglas Hunt
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Muhammad Safdar: Intelligent Transport Systems Research Center, Wuhan University of Technology, 1040 Heping Avenue, Wuchang District, Wuhan 430063, China
Ming Zhong: Intelligent Transport Systems Research Center, Wuhan University of Technology, 1040 Heping Avenue, Wuchang District, Wuhan 430063, China
Linfeng Li: Intelligent Transport Systems Research Center, Wuhan University of Technology, 1040 Heping Avenue, Wuchang District, Wuhan 430063, China
Asif Raza: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing 211106, China
John Douglas Hunt: Department of Civil Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada

Land, 2025, vol. 14, issue 4, 1-49

Abstract: Regional planning agencies increasingly rely on Spatial Economic Models (SEMs) to evaluate the impact of various policies. However, traditional SEMs often employ homogeneous technical coefficients (TCs) to represent technology patterns used by activities located in very different areas of a region, leading to misrepresentations of production and consumption behaviors, and consequently, inaccurate modeling results. To this end, we propose a Differential Spatial Economic Modeling (DSEM) framework that incorporates region-specific TCs for activities within Independent Planning Units (IPUs), such as provinces or cities, each characterized by unique economic, demographic, and technological features. The DSEM framework comprises three core components: (1) a regional economy model that forecasts activity totals for each IPU using economic and demographic forecasting model, supplemented by statistical analyses like the Gini index and K-means clustering to group activities from different IPUs into homogeneous ‘technology’ clusters based on their TCs; (2) a land use model that allocates IPU activity totals to corresponding traffic analysis zones (e.g., counties or districts) using the Differential Spatial Activity Allocation (DSAA) method. This determines the spatial distribution of commodities (such as goods, services, floor space, and labor) across exchange zones, balancing supply and demand to achieve spatial equilibrium in both quantity and price; and (3) a transport model that performs modal split and network assignment, distributing commodity trip origin–destination matrices across a multimodal transportation supernetwork (highways, railways, and waterways) using a probit-based stochastic user equilibrium assignment model. The proposed method is applied to a case study of the Yangtze River Economic Belt, China. The results demonstrate that the proposed DSEM yields better goodness-of-fit (R 2 ) values between observed and estimated flows compared to the traditional aggregate SEM. This indicates a more precise and objective representation of spatial economic activities and technological patterns, thus resulting in improved estimates of freight flows for individual transportation modes and specific links.

Keywords: integrated modeling; land use model; regional planning; Gini index; freight transportation; spatial economics; large-scale model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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