Estimation Of Large Regional Urban And Rural Population Density Based On Globeland30

The population density is an important basic data of urban planning, environmental protection, disaster prevention and reduction. Previous simulation of large regional population density mostly based on top of the administrative hierarchy of vector data, it is difficult to express population distribution in a better microscopic. Remote sensing data can better in the population density estimates of regional population, But there is less study about the estimation of population density by using remote sensing data for a wide areas or the whole world. Meanwhile, the estimation of population density is difficult to describe details of urban and rural population spatial distribution accurately.In order to resolve the problem above, an estimation method of large regional urban and rural population density, which is based on the first 30m global land cover dataset(GlobeLand30) is proposed. Based on the urban and rural area data partitioned from artificitial surfaces data in GlobeLand30 datasets, the population density were estimated in urban and rural area respectively. Urban population density was estimated through the correlation between night lighting intensity and population. Through area revise of rural patches by the method of quadrats estimation, the rural population density was estimated. This paper takes Shandong province as a test area. The result shows that the method of urban-rural population density estimation could reflect the heterogeneity and continuity of the population spatial distribution in urban internal well, and express the population spatial distribution in rural area. By comparison with the reference data, the method of this paper is superior to the reference data in describing the spatial extent of residents and expressing the spatial distribution of population. And due to the globality of GlobeLand30 data, it is feasible to extend the method to a wider area.