Method and system for estimating population density in urban built-up areas based on spatial big data collaboration

Abstract

The invention relates to a method and system for estimating the population density of urban built-up areas with spatial big data collaboration. The topological algorithm is used to divide the urban blocks, and combined with the spatial big data of the points of interest to distinguish the urban blocks into residential areas and non-residential areas; using remote sensing optical stereoscopic imaging data to obtain building heights; according to building heights and building ranges combined with demographic data, Construct a population density estimation model by multiple regression analysis; use the scope of the building and the height of the building as input variables, input it into the population density estimation model, calculate the population density, and then use the spatial statistical analysis method to distribute it to the regular grid space corresponding to the urban built-up area. The method and system can accurately and accurately estimate the population density of urban built-up areas, are more suitable for urban planning, disaster prevention and reduction, and business decision-making for fine population data, and are conducive to further promotion and application.

Description

technical field [0001] The invention relates to the technical field of urban remote sensing and urban demography, in particular to a method and system for estimating the population density of urban built-up areas with spatial big data collaboration. Background technique [0002] Population density distribution is the spatial manifestation of population process, and urban population density distribution and simulation are important contents in the study of urban spatial structure and suburbanization. Scholars at home and abroad have used mathematical models to reveal the general law of urban population density distribution based on the characteristics of "circle-type" cities. These studies analyze the spatial distribution of population density based on statistical data, assuming that the population is continuously and evenly distributed within the census area, but the actual population distribution is not continuous. Internationally, many institutions are committed to the re...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem that traditional population spatialization products based on land use / land cover data and optimized parameters cannot accurately describe the actual spatial distribution characteristics of population in urban built-up areas, the present invention provides a method for estimating the population density of urban built-up areas with spatial big data collaboration, Based on the range and height of buildings extracted from high-resolution optical remote sensing data and remote sensing optical stereoscopic imaging data, the population density estimation model is collaboratively constructed using road network and spatial big data of interest points, and the fine population density estimation of urban built-up areas is realized.

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