Elderly Residents’ Uses of and Preferences for Community Outdoor Spaces during Heat Periods

市中心 空格(标点符号) 老年人 人口 订单(交换) 人口老龄化 地理 老年学 心理学 应用心理学 业务 计算机科学 环境卫生 医学 操作系统 考古 财务
作者
Xiaolin Yang,Yini Fan,Dawei Xia,Yukai Zou,Yuwen Deng
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:15 (14): 11264-11264 被引量:9
标识
DOI:10.3390/su151411264
摘要

The downtown cores of many cities are characterized by aged communities that tend to host a relatively high population of elderly retirement residents. The availability and usage of outdoor spaces within these communities play a crucial role in promoting active aging, providing essential locations for rest, activities, and social interaction among the elderly. However, in the planning and design of these spaces, attention is often focused on the safety and mobility requirements of the elderly population, while a lack of research is apparent in the area of elderly-specific preferences for spaces designed for relaxation and communication. In this study, we selected an aging community as the research target and conducted a detailed investigation of the outdoor spaces where the elderly residents gather and build up spontaneously in summer. Our objective was to evaluate the environmental factors influencing the selection of these outdoor spaces by the elderly for relaxation and communication. We analyzed the correlations between these factors and the number of occupants in these spaces and developed predictive models accordingly. The findings indicate that the environmental factors impacting the utilization of outdoor spaces by the elderly during heat periods within the community are, in order of importance: temperature, relative humidity, human traffic flow, and noise levels. These factors include physical and social aspects; temperature is a negative correlation factor affecting the use of outdoor space by the elderly, and the rest are positive correlation factors. This shows that the elderly like to gather and chat in a cool, crowded, and lively environment. Through the data analysis, it was determined that the random forest regression model was the most effective in predicting the number of residents remaining in these spaces. With a coefficient of determination (R2) of 0.7958, the model can assist in community update planning and design, help in selecting outdoor spaces, and improve the quality of the outdoor environment. This study discusses the factors influencing the elderly’s use of community outdoor space from the physical and social levels, and the prediction model is significant for the optimization of spatial elements and spatial location.
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