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Using Wi-Fi probe and location data to analyze the human distribution characteristics of green spaces: A case study of the Yanfu Greenland Park, China

机译:使用Wi-Fi探测和位置数据来分析绿地的人体分布特征 - 以中国延府格陵兰公园为例

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摘要

Public open space constitutes a significant part of the sustainable urban environment. Urban green space-which includes parks, sports fields, and wetlands-is a crucial type of public open space in a healthy urban ecosystem. Most studies on urban green spaces comprise large-scale objective evaluations, with relatively few related theoretical studies from the perspective of human behavior. This is predominantly due to the technical constraints involved in obtaining small-scale public open space population activity data. To address this issue, this study examines the crowd activities of an urban green space by combining Wi-Fi probe and location data to discern population distribution characteristics. This study uses Yanfu Greenland Park, a green space in a central area of Shanghai-a typical high-density city-as a case study. This study proposes a technical method for measuring population distribution in a small-scale public space, demonstrating its applicability through an analysis of the population density distribution and activity trajectory in an urban green space. The methodology demonstrated in this study can help urban planning designers and managers create more successful public open spaces. This technical method may also assist urban planning and related research on different scales.
机译:公共开放空间构成可持续城市环境的重要组成部分。城市绿地 - 包括公园,体育场和湿地 - 是健康城市生态系统中公共开放空间的重要类型。大多数关于城市绿地的研究包括大规模的客观评估,与人类行为的角度相对较少的相关理论研究。这主要是由于获得小规模公共开放空间种群活动数据所涉及的技术限制。为了解决这个问题,本研究通过将Wi-Fi探测和位置数据结合到辨别人口分布特征来检查城市绿色空间的人群活动。这项研究采用了燕府格陵兰园,在上海市中心地区的绿色空间 - 典型的高密度城市 - 作为案例研究。本研究提出了一种用于测量小规模公共空间中人口分布的技术方法,通过分析城市绿地中的人口密度分布和活动轨迹来证明其适用性。本研究中展示的方法可以帮助城市规划设计师和管理者创造更成功的公共开放空间。这种技术方法还可以帮助城市规划和相关规模相关研究。

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