Abstract

Planning transportation networks between urban and rural areas is of crucial importance for the integration of urban and rural development, for socio-economic connectivity, and for sustainable growth. The study offers a model assembly approach in order to logically plan an integrated urban–rural transportation network that may support the coordinated development of its living–production–ecological space. Within this approach, the ordinary least squares (OLS) linear regression analysis method is used to investigate the correlation between urban and rural areas of a transportation network and the influencing factors in the living–production–ecological space so as to objectively analyze their degree of influence. These factors are size of town, urban and rural settlements, life services, supporting transportation facilities, trunk layout, external transport links, cargo hubs, logistics and transportation, enterprise distribution, agricultural production, terrain, distribution of water systems, tourism resources, heritage preservation, and ecological protection. The analytic hierarchy method is used to assign weight to the urban and rural transportation network planning impact index system. As a result, a transportation network planning decision hierarchy model is implemented to identify suitable areas for urban and rural transportation network construction and to provide guidance and reference for planning. Jiangxia District, Wuhan, China is selected as the study area to verify the feasibility and effectiveness of the model. The findings indicate that the influencing factors of urban and rural industrial and ecological space have a significant impact on the transportation network in the research area. Planning should prioritize optimizing the central region’s transportation network structure and enhancing traffic flow between urban and rural communities, which is effectively in line with the current reality. The suggested approach is helpful in establishing case-study-specific planning and development strategies of urban and rural integrated transportation networks in the age of big data, as well as in balancing these influencing factors in living, production, and ecological spaces when planning an integrated urban and rural transportation network.

Full Text
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