Delimitating the Natural City with Points of Interests Based on Service Area and Maximum Entropy Method.

Lingbo Liu,Zhenghong Peng,Hao Wu,Yang Yu,Binxin Xia,Jie Zhao

doi:10.3390/e21050458

Abstract

The natural city, which is essential to understand urban physical scale and identify urban sprawling in urban studies, represents the urban functional boundaries of the city defined by human activities rather than the administrative boundaries. Most studies tend to utilize physical environment data such as street networks and remote sensing data to delimitate the natural city, however, such data may not match the real distribution of human activity density in the new cities or even ghost cities in China. This paper suggests aggregating the natural city boundary from the service area polygons of points of interest based on Reilly’s Law of Retail Gravitation and the maximum entropy method, since most points of interests provide services for surrounding communities, reflecting the vitality in a bottom-up way. The results indicate that the natural city defined by points of interests shows a high resolution and accuracy, providing a method to define the natural city with POIs.

Highlights

The size of cites has multi-dimensional impacts on society, economy, and the environment, influencing energy and resource demands, urban congestion and biodiversity reduction [1,2]
It is noteworthy that service area of mobile phone base stations shows a more even feature former is planned thewhere government and is theplanned latter isby built the invisible hand of theismarket
What are the differences among natural city based geographic units? Is the mean the best threshold value? What are the differences among natural boundaries proposed by various kinds of city boundaries proposed by various kinds of POIs?

Summary

Introduction

The size of cites has multi-dimensional impacts on society, economy, and the environment, influencing energy and resource demands, urban congestion and biodiversity reduction [1,2]. Measuring human activities with traditional socioeconomic statistical data based on administrative boundaries is still prevalent, more and more research tends to identify urban boundaries with big data, such as remote sensing data, light imagery, road intersections, traffic connectivity, social network data, etc. [4,5,6] Such kinds of urban boundaries refer to the concept of “natural city” inspired by Alexander. This widely influential urban theorist has indicated that the city is not a tree, but rather a dynamic, open half-network structure, which establishes a complex network perspective for understanding cities beyond their administrative boundaries [7]. The method for measuring natural cities admits the inherent diversity, non-linear dynamics and essential aesthetic characteristics of urban fractals underlying the complexity of human settlements [8,9,10,11], focusing on human activity data of everyday life [12]

Results

Discussion

Conclusion