Abstract: The analysis of job-housing characteristics can provide important guidance for the formulation of urban development planning and solving urban traffic problems. Based on the big data of easygo, this paper takes the analysis of the characteristics of job-housing distribution and the characteristics of job-housing balance of the main urban area of Wuhan from three scales:urban cluster scale, street scale, and micro scale. The study found that:① At the cluster scale, the population distribution among clusters at each time period decreases sequentially from the center to the periphery, which is consistent with the spatial pattern of the circle development and cluster layout in the main urban area of Wuhan, and each cluster is in a state of job-housing balance. ②At the street scale, 65.58% of the streets in the main urban area are relatively balanced between jobs and housing, and a few streets have the phenomenon of job-housing imbalance. ③ At the micro-scale, combined with map and POI data analysis, the population during working hours is concentrated in the vicinity of commercial districts and traffic lines, and during rest hours, the population is relatively evenly dispersed in residential areas. Taking the hot spot of population gathering during working hours as an example, the employment of the hot spot is highly concentrated, and there is an employment-oriented job-housing imbalance. As the distance increases, the job-housing distribution tends to be balanced.

Key words: job-housing balance, job-housing distribution, easygo big data, kernel density analysis, population aggregation