Study on Job-Housing Spatial and Commuting Characteristics of Employment Centers in Guangzhou, China, Based on Multi-Source Data

Using Guangzhou, China, as an example, this paper combines big data such as mobile phone signaling data with traditional data including census data and residential questionnaire data and adopts a new means of crowd portrait to analyze the job-housing spatial and commuting characteristics of a typical job center in Guangzhou. The results show that the overall commuting characteristics are closely related to location, industry type, radiation capacity, housing supply and rail transit supply level, etc. There are obvious differences in job-housing spatial and commuting characteristics among different groups of people, so we should pay attention to the matching of the facilities' supply conditions of job centers and the needs of different groups of people. Accurate depiction of people's spatial and temporal portrait and different needs based on multi-source data will be an important means to optimize the job-housing relationship and improve residents' commuting efficiency in Chinese cities.