| LOW-CARBON TRANSPORTATION & GREEN DEVELOPMENT |
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Cluster characteristics analysis and critical node identification in ecologically integrated transport networks in urban agglomerations |
| MA Shuhong1,2, YANG Lei1, CHEN Xifang1, ZHU Min1 |
1. College of Transportation Engineering, Chang'an University, Xi'an 710064, China;
2. Key Laboratory of Transportation Industry for the Control and Recycling Technology of Transportation Network Facilities in Ecological Security Barrier Area, Chang'an University, Xi'an 710064, China |
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Abstract [Objective］ To achieve the integrated development of transport, economy, and ecological environment quality, it is necessary to identify the core clusters and key nodes properly in urban agglomerations. ［Methods］ In this paper, the Guanzhong Plain urban agglomeration is taken as the research object, and weights are assigned to the functional attractiveness of nodes, radiance, and carbon emission intensity through the entropy method. A modified gravity model based on the multidimensional characteristics of the integrated transport network nodes is constructed to calculate the strength of the spatial connections between districts and counties within the urban agglomeration. Furthermore, a model of spatially linked networks is constructed by combining the spatial structure theory with complex network theory. This model takes the skeleton of the comprehensive transportation network as the main body, the districts and counties as the nodes, and the indicators of transportation network level, functional attractiveness and radiance, and carbon emission correlation intensity as the connected edge weights having multidimensional and multilevel characteristics. Additionally, unnecessary parameter calculations are removed to improve the INFORMAP algorithm by combining the centralities of degree, betweenness, and closeness obtained from the complex network theory. This improved INFORMAP algorithm classifies regional clusters separately in terms of traffic, function, and carbon emissions. The result reflects the strength of the spatial linkages between the districts and counties of the urban agglomeration in different dimensions. Finally, based on the results of regional grouping and the hypergraph theory, we construct a hypergraph network model of ecologically integrated transport networks in urban agglomerations, and key indicators such as neighborhood hyper degree and neighborhood influence entropy are proposed to identify the key nodes of ecologically integrated transport networks in urban agglomerations. ［Results］ The high-speed railway, motorway, and mainline railway networks of the Guanzhong Plain urban agglomeration were divided into two clusters. The western cluster had a considerably lower frequency of intercity travel than the eastern cluster, and the Xi'an cluster had an increased transport network and frequency of intercity travel. The result of the high-level division of the transport network into clusters was mostly centered on prefecture-level cities. The spatial distribution pattern in terms of functions and carbon emission links had one pole and many cores, with Xi'an at the core. In terms of the relationship between cluster and administrative divisions, some districts and counties had broken through the constraints of higher administrative divisions to form independent groupings. Xi'an and Xianyang were key nodes in the construction of the ecologically integrated transport network of the city cluster. The importance of the nodes in the eastern cluster was found to be greater compared to the western part. ［Conclusions］ To achieve an integrated development pattern of transport, economy, and ecological environment quality in urban agglomerations, we optimize the layout of the existing transport network, increase the proportion of the low-grade transport network, supplement and connect the high-grade transport network through the articulation role of the low-grade transport network, and create an integrated multilevel transportation network pattern.
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| Keywords
traffic engineering
urban agglomeration
ecologically integrated transportation network
clusters
key nodes
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Issue Date: 16 October 2023
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2023,
Vol. 63
