使用谷歌街景纵向图像测量邻里障碍的变化:一个可行性研究
Pedro Gullón1,2, Dustin Fry3,4, Jesse J Plascak5
1Public Health and Epidemiology Research Group. Department of Surgery, Social and Medical Sciences. School of Medicine and Health Sciences, Universidad de Alcala, Alcala de Henares, Madrid, Spain.
Cities & health
|October 18, 2023
概括
纵向的谷歌街景 (GSV) 图像揭示了2009年至2019年期间费城越来越多的社区混乱. 这项研究表明GSV.
科学领域:
- 城市卫生 城市卫生
- 环境科学 环境科学
- 地理空间分析的研究.
背景情况:
- 邻居障碍与不利的健康结果有关.
- 纵向数据对于理解城市环境变化至关重要.
- 谷歌街景 (GSV) 提供了随着时间的推移跟踪城市变化的潜力.
研究的目的:
- 评估使用纵向GSV图像用于城市健康研究的可行性.
- 为了测量2009年至2019年期间费城大都会地区邻里混乱的变化.
主要方法:
- 审计了来自费城192个街段的GSV图像.
- 评估了2009年,2014年和2019年的图像可用性.
- 在每个时间点收集了8个邻里障碍指标,用于可用图像的部分.
主要成果:
- 超过70%的街段至少有一个GSV图像可用.
- 从2009年到2019年,社区混乱显著增加.
- 纵向的GSV数据捕捉了城市街景的时间变化.
结论:
- 纵向GSV图像是监测城市社区混乱的可行工具.
- 调查结果突显出一个令人担忧的趋势,即越来越多的社区混乱.
- 未来的研究应该探索这些观察到的变化的驱动因素.
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