Exploring Urban Spatial Hotspots’ Properties Using Inter-Connected User-Location Networks

Abstract

The rapid urbanization in recent years booms our daily life. However, great challenges still exist when it comes to resource allocation and urban planning. While there are lots of works on sensing urban spatial hotspots and exploring their properties, little attention has been given to users’ interactions with them from an inter-connected way. Users’ visits on places always reveal the places’ ability of grouping people together. We call it users and places are inter-connected. Benefiting from the development of information technology, we have observed a dramatic increase of the mobile big data. How to convert the data into actionable insights are some of the biggest impediments to unlock its value. Fully mining the mobile big dataset collected from one northern city in China, we first present a density-based method to recognize hotspots in a city, which are usually significant places with specific functions. Then a user-location inter-connected network is constructed based on the detected spatial hotspots. Different properties are shown in different places. Our analysis sheds light on the relationship between the prosperity of people and places, distinguishing various urban functions. Besides, it will benefit the next generation of location-based services and applications.