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Int. J. Environ. Res. Public Health 2016, 13(8), 833; doi:10.3390/ijerph13080833

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

1
Department of Geographic Information Science, Nanjing University, Nanjing 210093, China
2
Department of Resources Environment and Tourism Management, West Anhui University, Luan 237012, China
3
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210093, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Academic Editor: Jamal Jokar Arsanjani
Received: 2 June 2016 / Revised: 11 August 2016 / Accepted: 12 August 2016 / Published: 18 August 2016
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Abstract

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. View Full-Text
Keywords: healthcare facilities; network kernel density estimation; network K-function; street centrality; correlation analysis healthcare facilities; network kernel density estimation; network K-function; street centrality; correlation analysis
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MDPI and ACS Style

Ni, J.; Qian, T.; Xi, C.; Rui, Y.; Wang, J. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis. Int. J. Environ. Res. Public Health 2016, 13, 833.

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