Urban population distribution method based on building properties

Abstract

The invention discloses an urban population distribution method based on building properties. The method comprises the specific steps that all building information and building periphery interest point information in an electronic map are obtained according to an urban longitude and latitude coordinate range; the electronic map is queried targeting a certain population statistic region, coordinates of the population statistic region are determined, and the gross population in the region is queried; all buildings in the population statistic region are screened out according to building locations and boundary angle point coordinates of the population statistic region; social activity properties of the buildings are inferred; population attraction coefficients, at different time unit areas, of the buildings of different social activity property types are set, and the population in the population statistic region is distributed into each building in the region to obtain building-grade population distribution; and all population statistic regions in a city are traversed to obtain urban population distribution. The method is applied to building-grade urban population distribution, the problem of rough urban population distribution scale can be effectively solved, and population distribution timing difference is reflected.

Description

technical field [0001] The present invention relates to the technical field of population distribution estimation, and more specifically, to a method for urban population distribution based on building attributes. Background technique [0002] The spatial distribution of urban population is a fundamental work for studying human behavior under the influence of urbanization and evaluating urban environments and human interactions. At the government level, multiple census data present the characteristics of urban population distribution from a macro perspective, and provide a partial data basis for smaller-scale studies on urban population distribution. At the technical level, the massive interest points provided by the network electronic map provide another way for human behavior research. At the same time, the attributes of interest points reflect the social activity attributes of buildings and even the area to some extent, which makes building-based Attributes of urban popu...

AI Technical Summary

Problems solved by technology

Given that the census data mostly uses the street as the basic unit, the population distribution based on the census data is mostly based on the block as the smallest scale, which cannot reflect the characteristics and differences of the population spatial distribution at the building level

Secondly, the population distribution characteristics of buildings with different social activity attributes are obviously different during the day and night or even at different times, and traditional methods cannot reflect the temporal differences in population distribution.

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