Assessment of Spatial Accessibility to Residential Care Facilities in 2020 in Guangzhou by Small-Scale Residential Community Data

Danni Wang, Changjian Qiao, Sijie Liu, Chongyang Wang, Ji Yang, Yong Li and Peng Huang
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Danni Wang: Department of Resources and the Urban Planning, Xin Hua College of Sun Yat-Sen University, Guangzhou 510520, China
Changjian Qiao: College of Resources and Environment, Academician Workstation for Urban-Rural Spatial Data Mining, Henan University of Economics and Law, Zhengzhou 450046, China
Sijie Liu: Land and Resources Technology Center of Guangdong Province, Guangzhou 510075, China
Chongyang Wang: Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
Ji Yang: Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
Yong Li: Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
Peng Huang: Shenzhen Municipal Planning and Natural Resources Bureau-Bao’an Management Bureau, Shenzhen 518101, China

Sustainability, 2020, vol. 12, issue 8, 1-23

Abstract: Population aging has increasingly challenged socio-economic development worldwide, highlighting the significance of relevant research such as accessibility to residential care facilities (RCFs). However, a number of previous studies are carried out only on street (town)-to-district scales, which could cause errors of the accessibility to RCFs for a family. In order to improve the resolution to individual families, we measure and compare the accessibilities to RCFs based on 3494 residential communities and 169 streets of Guangzhou in 2020 through the two-step floating catchment area (2SFCA) method. It was found that the distributions of the elderly and the service-dense blobs of the RCFs show patterns of a three-level spatial distribution, with a characteristic clustering at the center with peripheral dispersion. The resultant accessibility to RCFs in Guangzhou, ranging from 2.5 to 3.45, is generally consistent with the studies focusing on street scales. However, the maximum difference in the accessibility of two residential communities on the same street ranges from less than 0.02 to 0.94 in Guangzhou, indicating large variations. Although the relative errors of the accessibility results based on bi-scale data are relatively low, the cumulative errors can be high, e.g., over 25% in many streets of large cities. Consequently, hundreds of elderly persons per street can be adversely affected by those errors, with six streets over 1000. Therefore, this study focusing on the smaller-scale residential community data may provide more accurate reference to individual households. For the spatial allocation and optimal layout of Guangzhou and similar cities with population aging, we suggest maximizing RCFs in metropolises by taking full advantage of existing residential care facilities with necessary restructuring, improvements, and expansions on service capability. While for less connected cities, we encourage building new RCFs in situ.

Keywords: spatial accessibility; residential care facilities; residential communities; population forecast; Guangzhou (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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