This article uses panel data from 31 provinces in China to explain the impact of urbanization on Chinese housing prices through ordinary least squares (OLS). In this paper, we decompose urbanization into transportation convenience, road quality, road density, education density and education level to explain in detail the impact of various aspects of urbanization on housing prices. At the same time, considering the spatial correlation, the Spatial Error Model model(SEM) is used to analyze the variables, and the results indicate that the neighboring cities also have corresponding effects on the city's housing prices. The results of the analysis are that traffic convenience, road quality, road density, education density, and education level that decompose the level of urbanization increase the housing price in China, and the neighboring cities also have a corresponding effect on the urban housing price. In addition, changes in household savings, wage levels, real estate investment and land supply all have various effects on housing prices. The analysis shows that the wage level plays a large role in raising the house price.