Salgado Ariel, Yuan Ziyun, Caridi Inés, González Marta C
Instituto de Cálculo, UBA-CONICET, Ciudad de Buenos Aires, Argentina.
Department of Landscape Architecture and Environmental Planning, UC Berkeley, California, US.
EPJ Data Sci. 2022;11(1):42. doi: 10.1140/epjds/s13688-022-00351-9. Epub 2022 Jul 18.
This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city's information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities' distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities' tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.
The online version contains supplementary material available at 10.1140/epjds/s13688-022-00351-9.
这项工作提出了一个便携式框架，用于通过二分加权网络估计潜在的公园需求和公园暴露情况。我们使用移动性信息和开放空间信息。移动性信息以从基于通话详单记录（CDR）的模型中采样的日常活动的形式出现。空间信息包括通过开放街道地图多边形表示的公园和2010年美国十年一次人口普查的普查区。该框架将每个城市的信息汇总到一个二分加权网络中，链接权重表示在平均工作日从每个普查区到一个公园的潜在访问次数。我们在疫情前的情景下比较了大洛杉矶地区和大波士顿地区的公园暴露情况和公园需求。一个普查区的公园暴露量计算为其居民日常活动周围的公园数量。一个公园的需求计算为其周围的日常活动数量。我们发现，两个城市的公园暴露分布形状相似，波士顿的平均值更高。另一方面，尽管两个城市的公园空间分布不同，但公园需求的分布非常相似。我们纳入了人口普查中的种族/族裔信息，以探讨公园暴露如何连接不同种族/族裔群体的区域。我们根据每个群体的游客数量将公园与种族/族裔群体相关联。少数族裔区域内的公园大多由多数群体使用。最后，通过检测网络中的社区，我们发现公园暴露在本地连接了城市，将公园与其附近的区域联系起来。此外，我们发现洛杉矶的网络社区与不同的种族/族裔构成之间存在显著的空间相关性。这样，公园暴露模式再现了城市人口群体之间的隔离。
在线版本包含可在10.1140/epjds/s13688-022-00351-9获取的补充材料。
