Simulation of urban population distribution grid by integrating geodetector and random forest model

doi:10.13474/j.cnki.11-2246.2020.0016

Abstract

Abstract: Fine population distribution is important to urban resource allocation and management.In this paper,we take the Yuexiu District, Liwan District, Tianhe District, Haizhu District, Baiyun District and Huangpu District of Guangzhou city as the research areas,and base on multi-source data such as demography, night lighting, interest points and land use,using the geodetector to identify the influencing factors of population distribution,and simulate the population distribution grid by using random forest model.The results show that compared with the traditional correlation analysis, the geodetector can identify the important factors of spatial distribution of population more accurately.The correlation coefficient between the results of population distribution grid simulation based on random forest model and the actual population of streets (towns) is 0.774, with an average relative error of about 30%.Compared with the simulation results based on linear regression model, the accuracy of the stochastic forest model is significantly improved.

Key words: population distribution, grid, simulation, random forest, geodetector

CLC Number:

P208

CHENG Fanglong, ZHAO Guanwei, YANG Muzhuang, LIU Yueliang, LI Fang. Simulation of urban population distribution grid by integrating geodetector and random forest model[J]. Bulletin of Surveying and Mapping, 2020, 0(1): 76-81.

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