China's rapid urbanization and economic development have given rise to the fast growth of the floating population, and housing is a key issue in the process of their integration into the destination cities. This paper intends to explore this topic by analyzing the spatial patterns of housing conditions of the floating population. Based on the sixth census data, the paper selects six indicators to measure housing conditions of the floating population: the home-ownership rate, the rental-housing rate, the floor area index, the housing facilities index (constructed by summing up the situation of five variables: availability of running water, washroom, bathroom, kitchen, and the type of fuel), the index of privacy (constructed by summing up the situation of two variables: the function of the dwelling and the number of the dwelling's floors), and the housing consumption index. It uses the methods of Spatial Autocorrelation Analysis and Hierarchical Cluster to examine the spatial distribution and agglomeration patterns of the floating population's housing conditions. The results of the calculation show that compared with urban permanent residents, members of the floating population are much more likely to live in rental homes;their housing conditions are generally worse;and their rental expenses are higher. The spatial variation of the homeownership rate, the rental-housing rate, and the housing facilities index is mainly manifested as north-south differences;the floor area index, and the index of privacy show marked difference between eastern and western China. The low-value centers of the housing consumption index are located in Inner Mongolia, Shaanxi, Hubei and Anhui provinces, while the high-value centers are located in Beijing. Furthermore the results of Spatial Autocorrelation Analysis demonstrate that there is a significant positive spatial correlation in the indicators of the floating population's housing conditions on a national scale, and identify the phenomenon of their spatial clustering and the centers of such spatial clustering. The analysis of Hierarchical Clustering identifies the housing conditions of the floating population into four distinctive groups, and suggests that the housing conditions of the floating population in the inner and east parts of China are better than those in the outer and west parts, and such a spatial variation extends from the north to the south. Finally, on the basis of the above findings, the paper puts forward some policy suggestions for improving the housing conditions of the floating population.
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