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

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.

Open Data Based Urban For-Profit Music Venues Spatial Layout Pattern Discovery

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Determination of gaps in the spatial accessibility of nursing services for persons over the age of 65 with lowered self-sufficiency: Evidence from the Czech Republic

“…The majority of residential facilities for senior citizens were established in the main cities whereas a lot of rural areas had a lower or just average supply of such services. According to [ 32 ], low accessibility of facilities for the care of senior citizens is caused not only by a low number of facilities, but also by their uneven spatial distribution.…”

An Analysis of Spatial Accessibility Changes According to the Attractiveness Index of Public Libraries Using Social Media Data

“…Luo [17] used the Huff model to clarify the population selection for services and conducted an accessibility analysis considering the demand side. Recently, in recognition of the fact that the analysis unit should be considered when analyzing accessibility, Bryant and Delamater [18] and Wang et al [19] conducted studies in which the analysis unit was related to the distance at either the macro-or micro-level. In addition, for travel cost, the spatial accessibility of public facilities such as healthcare facilities was assessed either by only making calculations in single-car mode [20,21], or by considering multiple transportation modes [15,22], such as public transportation, cycling and walking as well as traveling by private car.…”