Method for estimating spatial and temporal distribution of urban population based on nighttime light remote sensing data

Abstract

The invention relates to a method for estimating the spatial and temporal distribution of urban population based on nighttime light remote sensing data. Nighttime lighting data of urban areas are extracted; modeling is carried out on all year-by-year urban population data and a regression equation of a total lighting value and urban population time is established, and population prediction is carried out based on the regression equation; rough spatial distribution of the population is obtained based on the extracted nighttime lighting data of urban areas; spatial clustering is carried out on the nighttime lighting data; and points with the adjacent spatial positions and similar light values are clustered into one class to obtain a clustering result, statistics of each kind of weighted average light values is carried out, wherein the higher the average value, the corresponding urban scale larger. According to the invention, a defect of low time resolution of the traditional statisticaldata is overcome based on the urban population after regression model prediction. Besides, spatial expression is carried out on the population by lighting data, so that defects of low spatial resolution and unapparent spatial distribution characteristics of the traditional statistical data are overcome.

Description

technical field [0001] The invention belongs to the field of nighttime light remote sensing data processing, in particular to a method for estimating the spatiotemporal distribution of urban population based on nighttime light remote sensing data. Background technique [0002] Population is an important factor in urban development, and scientific and effective population management is of great significance to the development of all aspects of the city. In recent years, the pace of urbanization in my country has accelerated, and the requirement for population data is particularly important. my country's population data is collected and managed through the national census and administrative divisions as the basic unit. There are two problems in practical application: 1. The time resolution is low, the census data update cycle is long, and real-time population data cannot be provided ; 2. The spatial resolution is low, and it is impossible to visually see the differences in pop...

AI Technical Summary

Problems solved by technology

This method also does not consider the problem of time, and its spatial grid is transformed into a population distribution in the overall space, and the approximate spatial distribution can be seen, but the population concentration center of each region cannot be clearly defined.

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