Extracting Spatial Interaction Patterns between Urban Road Networks and Mixed Functions

TL;DR

This study introduces a framework to analyze how the structure of urban road networks influences the spatial distribution of mixed urban functions, using Beijing's road and POI data to reveal key patterns.

Contribution

The paper presents a novel method combining POI data and graph theory to quantify the influence of road network sub-structures on urban function aggregation.

Findings

Higher road network degree correlates with increased function aggregation.

Diversified local degrees promote urban function clustering.

Proximity to city center affects mixed function distribution.

Abstract

In the field of urban planning, road network system planning is often the first step and the main purpose of urban planning is to create a spatial configuration of different functions such as residence, education, business, etc. Generally speaking, the more mixed the functions of an area has, the more possible its vitality may be. Therefore, in this article, we propose a new framework to study the specific spatial influence patterns of the overall structure and different sub-structures of road networks on the mixed functions. Taking road segment as the basic unit, we characterize mixed functions aggregation of road networks with the number of POIs categories within 100 meters around every road segment. At the same time, on the basis of centrality measurement in graph theory, we use 4 indexes to reflect the characteristics of the urban road network structure, including degree, closeness, betweenness, and length. We conduct our methods and experiments using the road networks and POI data within the 5th ring road of Beijing. The results demonstrate that urban road networks inherently influence the aggregation of urban mixed functions in various patterns and the patterns of road network sub-structures is also quite different. Our study shows that the higher the degree of the road network structure has, the more likely it will attract functions' aggregation. It also reveals that diversified local degree will help gather urban functions. In addition to those, the analysis as well validates the importance of small-grids typology of urban road networks and the closeness to the center of cities.