Complex city interaction network model with distance decay and spatial

Authors: Yuxia Wang*, Peking University, Yu Liu, Institute of Remote Sensing and Geographic Information Systems, Peking University, Beijing, China, Fahui Wang, Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, USA
Topics: Geographic Information Science and Systems, Urban Geography, Urban and Regional Planning
Keywords: Urban geography, complex city network, distance decay effect, spatial agglomeration effect.
Session Type: Paper
Day: 4/11/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Bayside A, Sheraton, 4th Floor
Presentation File: No File Uploaded


The size of cities is well known as a fundamental role for their social and economic interactions with others. And the fact that many complex network connectivities follow a scale-free distribution property has been proved by combining the underlying growth mechanism and preferential attachment ingredients. While for the complex city system, a city is more apt to connect with its near cities and a large metropolitan group is more attractive to a new connecting city, so the distance decay effect and spatial agglomeration effect might affect and reshape the city interaction network differently. So in this paper, a complex network model is proposed based on the distance decay and spatial agglomeration effect, and their effectiveness has been verified by mathematical demonstration and empirical data. First of all, distance decay effect and their spatial positions are absorbed in our model to improve the traditional non-geographic complex network model and then their connectivity distributions are compared. Secondly, theoretical analysis are made to express the distance decay effect in a mathematical method and compare it with the basic complex network. Finally, empirical dataset is utilized to check out the proposed complex geographical network model. Results shows that our model validates the relationship of the interaction probability with the city size considering the distance decay effect and the spatial agglomeration effect and has shown its effectiveness in delineating the city connectivity distributions.

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