Analysis of Community Living Circle Measurement Method and Influencing Elements Based on Location-Based Services Data

Abstract:

The delimitation of the boundary of the living circle is both the focus and the difficulty in the study of community living circles. There are three existing delimitation methods， administrative boundaries or regulatory planning units， service radius and accessibility of facilities， and daily activities of residents， of which the daily activities of residents are the closest to the original definition of the community living circle. However， the current application of this method mainly relies on the data of the global positioning system （GPS）， which is costly and limited in sample size， making it difficult to describe the activity patterns of most residents in a community and lacking a comprehensive understanding of a wide range of different types of community living spheres. In this paper， based on the large sample of the data of location-based services （LBS）， a complex network analysis technique is used to measure the community living circle in the central city of Chengdu （549 km²）， and by identifying its scale and boundary features， the spatial factors such as location， road network density and point of interest （POI） density on the community living circle are further explored. The results show that better network clustering results （close to the actual size of a 15-minute living circle） can be obtained by choosing carefully the unit resolution and distance constraint d-values. The size of community living circles classified based on LBS data varies widely， but most of the sizes are between 1 and 5 km². Among the three types of representative spatial elements， road network density and community living circle size， there is a moderate correlation， and location and commercial POI density are not significantly correlated with the size of the community living area. However， there exists a strong correlation between these three spatial elements and population density of community living circle. This paper reveals that community living circle measurement method based on LBS data， will deepen our understanding of the community living circle phenomenon and provide theoretical and technical support for community living circle planning.

Key words:community living circle;social network analysis;measurement;feature identification