Simulation of Village-Level Population Distribution Based on Land Use: A Case Study of Hefeng County in Hubei Province

  • Beijing key Laboratory of Resource Environment and Geographic Information System, Capital Normal University;Key Laboratory of 3-Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University;State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China

Received date: 2013-12-11

  Revised date: 2014-02-19

  Online published: 2014-05-10


The problem that population data is usually missing in small scale areas such as administrative villages which are always mentioned in population distribution studies and related researches. In this context, we took the Hefeng County in Hubei Province as the study area and analyzed the correlation between land use type index and population density. The simulation of the village-level population distribution is performed using Geographically Weighted Regression (GWR) method, grid method and BP neural network method respectively. Then, from the perspective of global-local and linear-nonlinear, the comparative precision validation was taken to verify the simulation accuracy of the population in villages with missing population data, which utilizes cross-validation method between the simulated population and the actual population. Results show that: (1) in all kinds of land use types, the main factors affecting population distribution are farmland, woodland, urban industrial land, and transportation land;(2) with regard to the three simulation methods we concerned, the errors of the simulated total population using these methods are all less than 3% for the 30 invested villages. By comparing the ratios of estimated values to the actual values of population in each village, and taking 10% as the tolerance, the reliability of GWR method is 43.33%, while grid method is 76.67% and BP neural network is 86.67 %. It shows that the BP neural network method is the optimal method among the three methods for the study area, and grid method is better than GWR method. In addition, the prediction accuracy of nonlinear regression is higher than that of linear regression;(3) population spatial distribution in the study area shows a high spatial positive correlation and a "high–high"agglomeration type which is also the main type in the study area;moreover, it shows that the population densities of the county are not spatially independent but intensively agglomerated.

Cite this article

ZHANG Jianchen, WANG Yanhui . Simulation of Village-Level Population Distribution Based on Land Use: A Case Study of Hefeng County in Hubei Province[J]. Journal of Geo-information Science, 2014 , 16(3) : 435 -442 . DOI: 10.3724/SP.J.1047.2014.00435


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