区域发展

基于手机定位数据的西宁市老年人公园绿地可达性预测

  • 赵志远 ,
  • 丁逸尘 ,
  • 杨喜平 ,
  • 吴升
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  • 1.福州大学数字中国研究院(福建),福建 福州 350003
    2.空间数据挖掘与信息共享教育部重点实验室,福建 福州 350003
    3.海西政务大数据应用协同创新中心,福建 福州 350002
    4.自然资源部城市国土资源监测与仿真重点实验室,广东 深圳 518000
    5.陕西师范大学地理科学与旅游学院,陕西 西安 710119
赵志远(1989-),男,博士,副研究员,主要从事人群动态观测与应用建模等方面的研究. E-mail: zyzhao@fzu.edu.cn

收稿日期: 2022-12-22

  修回日期: 2023-02-22

  网络出版日期: 2023-11-10

基金资助

国家自然科学基金项目(42201500);国家自然科学基金项目(42271468);福建省中央引导地方科技发展专项(2020L3005);空间数据挖掘与信息共享教育部重点实验室开放基金(2022LSDMIS03);自然资源部城市国土资源监测与仿真重点实验室开放基金资助课题(KF-2022-07-005)

Prediction of the accessibility of parks and green spaces for the elderly in Xining City based on mobile phone location data

  • Zhiyuan ZHAO ,
  • Yichen DING ,
  • Xiping YANG ,
  • Sheng WU
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  • 1. Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350003, Fujian, China
    2. Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou 350003, Fujian, China
    3. Fujian Collaborative Innovation Center for Big Data Applications in Governments, Fuzhou 350002, Fujian, China
    4. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518000, Guangdong, China
    5. School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, Shaanxi, China

Received date: 2022-12-22

  Revised date: 2023-02-22

  Online published: 2023-11-10

摘要

预测并分析老年人公园绿地资源可获取性对提高老年人生活品质、有效应对我国老龄化社会带来的有关挑战具有重要意义。为使城市公园绿地的分布更具“适老性”,基于西宁市带有年龄标识信息的手机位置数据,识别并预测老年人口的空间分布,运用高斯两步移动搜索法对老年人公园绿地可达性进行研究及预测。结果表明:(1) 2018—2028年老年人数显著增加,且老年人数变化量呈现中心城区及远郊区较低、近郊区高的环状分布特征。(2) 10 a间,老年人公园绿地可达性的空间分布总体格局未发生显著变化,但可达性水平总体下降。(3) 2018—2028年老年人公园绿地可达性相对变化量较大,步行和公交30 min条件下,约87%的空间单元的公园绿地可达性降低超过70%。研究结果补充了高空间精度下城市老年人公园绿地可达性研究的不足,提供了面向老龄化发展需求的城市未来公园绿地规划建议。

本文引用格式

赵志远 , 丁逸尘 , 杨喜平 , 吴升 . 基于手机定位数据的西宁市老年人公园绿地可达性预测[J]. 干旱区地理, 2023 , 46(10) : 1744 -1756 . DOI: 10.12118/j.issn.1000-6060.2022.672

Abstract

Predicting and analyzing the availability of green space resources for the elderly are crucial for improving their quality of life and addressing the challenges of an aging society. Taking Xining City, the area with the largest elderly population in Qinghai Province, as the study area, this study identifies and predicts the spatial distribution of older people based on mobile phone location data with age identification information. The Gaussian-based two-step floating catchment area (G2SFCA) method was then employed to study and predict the accessibility of parks and green spaces for the elderly. The following results were observed: (1) The elderly population increasing rate exhibited a circular distribution, displaying a low rate in the central city and outer suburbs and a high rate in the inner suburbs. (2) The overall spatial distribution pattern of accessibility of parks and green spaces for the elderly did not change significantly over the 10-year forecast period, but the general accessibility level declined. Under the condition of walking for 15 min, the population covered by relatively high and high grades of accessibility decreased from 17.58% to 6.70%. Moreover, under the condition of public transportation for 30 min, the population covered by relatively high and high grades of accessibility decreased from 26.41% to 9.28%. (3) It was found that the relative variability of accessibility of parks and green spaces for the elderly is significant from 2018 to 2028, with approximately 87% of the parks and green spaces experiencing a reduction of >70% in accessibility under both walking and public transportation conditions for 30 min. This study provides valuable insights for future urban park and green space planning, particularly in response to the needs of an aging population.

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