Research on urban vacancy rate based on luminous remote sensing data: a case study in Beijing

The vacancy rate of urban housing is an important indicator for evaluating the health of the real estate market. If traditional survey methods are used to conduct on-site surveys on whether housing is inhabited, it will require a lot of manpower and financial resources. This study proposes an estimation method for urban housing vacancy rate based on nighttime light data from the night light remote sensing satellite Luojia-1. The research area of this case study is divided into four regions within the Fifth Ring Road in Beijing, with the ring road as the boundary. By combining the Luojia-1 night light remote sensing data with urban building data, a new index called "Building Land Index" (CLI) was introduced to express the proportion of building area per unit area; A new weight index called "Urban Area Index" (UAR) was introduced using GlobeLand30 data and Luojia-1 night light image data to represent the city density of pixels, which was used to correct the night light data to more accurately represent the city's light intensity; Select the average light intensity of areas with a housing vacancy rate of 0 within the study area as the 'Light Intensity Index' (NLI) for the study area. So we can use it to achieve periodic monitoring and spatiotemporal analysis of housing vacancy rates