House vacancy at urban areas in China with nocturnal light data of DMSP-OLS

Night light brightness value by remote sensing has been important data source for urban context studies owning to be objective, real time, low cost and connection with spatial data easily. Housing is a critical issue for urban development. House vacancy can be calculated by two indicators. One of which is using houses, and another one is total houses. Night light data and house price will be employed to do the calculation of house vacancy. The authors of this paper would like to compare data of night light brightness value with DMSP-OLS and house price with statistic report within fifty cities in China, as well as analyze the pops issues of real estate industry among these cities with remote sensing and GIS techniques to get boundaries and the brightness value of them, While correlation and regression analysis will be employed to conducted the result. The conclusion like that: there are big gaps of using house and owing house. Efficient policy for solving housing problem depends on the decisions of local authorities of cities.