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| 老年人公交移动性的季节时空分异特征研究——以安徽省芜湖市为例 | |
| 引用本文： | 李智轩,甄峰,张姗琪,杨羽.老年人公交移动性的季节时空分异特征研究——以安徽省芜湖市为例[J].地理科学进展,2021,40(2):293-303. |
| 作者姓名： | 李智轩 甄峰 张姗琪 杨羽 |
| 作者单位： | 1. 南京大学建筑与城市规划学院,南京 210093 2. 江苏省智慧城市设计仿真与可视化技术工程实验室,南京 210093 3. 研车数据科技(江苏)有限公司,南京 210046 |
| 基金项目： | 国家社会科学重点基金项目(20AZD040);中国博士后科学基金项目(2019M651784);中央高校基本科研业务费专项基金 |
| 摘 要： | 移动性是老年人生活质量的重要影响因素,提高老年人的移动性是延长老年人独立生活时间,从而减小社会养老成本的重要手段。公共交通是中国老年人较长距离出行的最主要交通方式,但已有研究对公交移动性的关注较少。论文从季节时空分异的角度出发,利用安徽省芜湖市智能公交卡数据,分析不同季节老年人公交移动性静态空间集聚特征以及季节变化条件下移动性变化值的空间集聚特征。结果表明：① 老年人公交移动性空间集聚明显,呈现圈层式分布的特征。不同季节、不同移动性指标在城市中心、城市中心外围和城市边缘的集聚现象存在较大差异。② 老年人公交移动性的时空分异现象是复合的,不同城市空间对季节变化的敏感程度存在差异,主要呈现出从城市中心向外递增的趋势。研究公交移动性的季节时空分异现象可以为老年友好型城市的规划建设提供更加适当的规划和灵活的政策建议。 |
| 关 键 词： | 公交移动性 老年人 时空分异 季节 芜湖市 |
| 收稿时间： | 2020-03-23 |
| 修稿时间： | 2020-07-18 |
Seasonal and spatiotemporal differences in the public transport-based mobility of elderly population: A case study of Wuhu City in Anhui Province |
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| LI Zhixuan,ZHEN Feng,ZHANG Shanqi,YANG Yu.Seasonal and spatiotemporal differences in the public transport-based mobility of elderly population: A case study of Wuhu City in Anhui Province[J].Progress in Geography,2021,40(2):293-303. | |
| Authors: | LI Zhixuan ZHEN Feng ZHANG Shanqi YANG Yu |
| Institution: | 1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China 2. Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Nanjing 210093, China; 3. Yakka System & Technology (Jiangsu) Co., Ltd, Nanjing 210046, China; |
| Abstract: | Mobility is an important factor that influences the quality of life of elderly population. Improving the mobility of the elderly is an important means to prolong their independent living time and thereby reduce the cost of elderly care of the society. Public transport is the most important transportation mode for the Chinese elderly population when they travel for a long distance. Despite many studies focusing on the elderly's mobility through walking, insufficient attention has been paid to the public transport-based mobility. This study took Wuhu City as the study area and examined the pattern of the elderly's public transport-based mobility using smart card data. In particular, three parameters—movement radius, movement frequency, and movement entropy—were first used to quantify elderly's public transport-based mobility. Spatial autocorrelation methods were applied to analyze how elderly's public transport-based mobility patterns are spatially aggregated in different seasons and how the patterns vary under seasonal changes. The results show that: 1) Elderly's public transport-based mobility shows an obvious spatial aggregation pattern. The clusters are circularly distributed across the city, with the city center, the periphery of the city center, and the edge of the city showing different aggregation characteristics. Specifically, the radius of movement shows a crossed distribution of cold spots and hot spots from the city center to the outskirts of the city; the movement frequency and movement entropy show a wide range of hot spots in the city center and the periphery of the city center, while the cold spots are distributed in groups on the edge of the city. The agglomeration characteristics did not show structural changes in different seasons, but there were differences in the location and range of agglomeration. 2) The spatiotemporal differentiation of the elderly's public transport-based mobility is compound. Although the overall influence of seasonal factors on the mobility of the elderly population is weak, there is a significant concentration in specific places. However, the sensitivity of different urban spaces to seasonal change is different, and it mainly increases from the city center outward. The study enriches elderly mobility research by developing an understanding on public transport-related mobility behavior of the elderly, and by exploring the spatiotemporal differentiations of public transport-based mobility across seasons. Empirically, this study can shed light on planning strategies and policy recommendations for developing elderly-friendly cities. |
| Keywords: | public transport-based mobility elderly population spatiotemporal differentiation season Wuhu City |
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