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GEOGRAPHICAL RESEARCH >

2014 , Vol. 33 >Issue 3: 520 - 531

DOI: https://doi.org/10.11821/dlyj201403011

High spatial resolution population distribution simulation based on building information and multi-agent

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  • 1. Center of Integrated Geographic Information Analysis, Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;
    2. School of Geography Sciences, Guangzhou University, Guangzhou 510006, China

Received date: 2013-03-22

  Revised date: 2013-09-23

  Online published: 2014-03-10

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Abstract

Knowledge of population distribution is essential for understanding and responding to many social, political, economical and environmental problems. Many studies have been done to estimate population distribution. However, most of the existing methods cannot produce high spatial resolution results or require data which are difficult to acquire. In this paper, we present a method of simulating high spatial resolution population distribution, which uses a multi-agent model based on building information. Firstly, simulation environment of the multi-agent model is constructed based on building information, such as height, area, density; Secondly, the property and behavior rules are defined, based on statistical data and survey reports; Finally, the multi-agent model is used to simulate population distribution of a community named Tairi, which is located in Fengxian District, Shanghai. Results prove that our multi-agent population model is capable of producing high spatial resolution population distribution results at acceptable accuracy level. The method is highly automated and the data it requires are easily available, thereby it has great potential of application.

Key words： population distribution; population density; high spatial resolution; multi-agent; building

Cite this article

ZHUO Li, HUANG Xinrui, TAO Haiyan, WANG Fang, XIE Yuhang . High spatial resolution population distribution simulation based on building information and multi-agent[J]. GEOGRAPHICAL RESEARCH, 2014 , 33(3) : 520 -531 . DOI: 10.11821/dlyj201403011

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