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基于两步移动搜索法的西安市社区卫生服务设施空间可达性评价。

Two-Step Floating Catchment Area Model-Based Evaluation of Community Care Facilities' Spatial Accessibility in Xi'an, China.

机构信息

School of Human Settlement and Civil Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

Int J Environ Res Public Health. 2020 Jul 14;17(14):5086. doi: 10.3390/ijerph17145086.

Abstract

Due to the rapid increase in the number of elderly people in Chinese cities, the development and planning of aged care facilities, and particularly community care facilities, which will gradually become the mainstream choice for the elderly in China, is becoming an important topic for urban sustainability. Previous studies have shown that the number and scale of aged care facilities in many cities are far from meeting the needs of the elderly and the overall occupation rate is low. Some of these cities are still expanding and some are undergoing urban renovation. In this process, the scientific planning of community care facilities to promote efficient use of facility resources has become an urgent problem that needs to be solved. In this study, the two-step floating catchment area (2SFCA) method and a potential model based on the Geographic Information System (GIS) were used to carry out a scientific evaluation of the spatial accessibility of community care facilities in the Beilin district of Xi'an. The aims were to explore the best quantitative research methods for assessing the distribution of Xi'an community care facilities' spatial accessibility, provide ideas for similar studies in the future, and further the understanding of spatial allocation of urban community care facilities resources.

摘要

由于中国城市老年人口数量的迅速增加,老年护理设施的开发和规划,特别是社区护理设施,将逐渐成为中国老年人的主流选择,因此成为城市可持续发展的一个重要课题。以往的研究表明,许多城市的老年护理设施的数量和规模都远远不能满足老年人的需求,整体入住率较低。其中一些城市仍在扩张,而另一些城市正在进行城市改造。在这个过程中,科学规划社区护理设施以促进设施资源的高效利用成为一个亟待解决的问题。本研究采用两步浮动集水区(2SFCA)方法和基于地理信息系统(GIS)的潜力模型,对西安市碑林区社区护理设施的空间可达性进行了科学评价。目的是探索评估西安市社区护理设施空间可达性分布的最佳定量研究方法,为今后的类似研究提供思路,并进一步了解城市社区护理设施资源的空间配置。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e46/7399904/0be919c85102/ijerph-17-05086-g001.jpg

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