Urban Functional Area Division Based on Cell Tower Classification

Abstract

Each city can be divided into different functional areas for different purposes, such as commercial areas, residential areas, leisure areas, office areas, etc. How to correctly divide these areas is very helpful for urban self-cognition and urban planning. Mobile phones have become almost a must-have for everyday life nowadays in big cities. People carry their mobile phones all the time, making phone calls and surfing on the Internet. For this reason, the Open Information Dynamic Data (OIDD) is a more representative indicator of the mobility characteristics of the population. In this study, we use the user, time and location information extracted from OIDD data to analyze and divide the urban functional areas for the purpose of understanding the regional composition of the city. We use the Latent Dirichlet Allocation (LDA) model and incorporate time and space information into the Dirichlet distribution to participate in the model hypothesis. This allows for the model's high-level analysis capabilities to exploit potential urban area functions through human mobility patterns.

Keywords

• Open information dynamic data
• human mobility
• mode mining
• region divide
• temporal and spatial analysis