Acta Geodaetica et Cartographica Sinica >

2015 , Vol. 44 >Issue 1: 82 - 90

DOI: https://doi.org/10.11947/j.AGCS.2015.20130538

The Visualization and Analysis of POI Features under Network Space Supported by Kernel Density Estimation

  • YU Wenhao ,
  • AI Tinghua
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  • School of Resources and Environmental Science, Wuhan University, Wuhan 430079, China

Received date: 2013-12-03

  Revised date: 2014-05-25

  Online published: 2015-01-22

Supported by

The National High-tech Research and Development Program of China (863 Program) (No. 2012AA12A404) The National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2012BAJ22B02-01)

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Abstract

The distribution pattern and the distribution density of urban facility POIs are of great significance in the fields of infrastructure planning and urban spatial analysis. The kernel density estimation, which has been usually utilized for expressing these spatial characteristics, is superior to other density estimation methods (such as Quadrat analysis, Voronoi-based method), for that the Kernel density estimation considers the regional impact based on the first law of geography. However, the traditional kernel density estimation is mainly based on the Euclidean space, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. Hence, this research proposed a computational model of network kernel density estimation, and the extension type of model in the case of adding constraints. This work also discussed the impacts of distance attenuation threshold and height extreme to the representation of kernel density. The large-scale actual data experiment for analyzing the different POIs' distribution patterns (random type, sparse type, regional-intensive type, linear-intensive type) discusses the POI infrastructure in the city on the spatial distribution of characteristics, influence factors, and service functions.

Key words： network kernel density; POI analysis; network analysis; spatial statistics

Cite this article

YU Wenhao , AI Tinghua . The Visualization and Analysis of POI Features under Network Space Supported by Kernel Density Estimation[J]. Acta Geodaetica et Cartographica Sinica, 2015 , 44(1) : 82 -90 . DOI: 10.11947/j.AGCS.2015.20130538

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