Li Zhenlong, Huang Xiao, Ye Xinyue, Li Xiaoming
Geoinformation and Big Data Research Lab, Department of Geography, University of South Carolina, Columbia, SC, USA.
Department of Geosciences, University of Arkansas, Fayetteville, AR, USA.
ArXiv. 2020 Nov 26:arXiv:2011.12958v1.
Understanding human mobility dynamics among places provides fundamental knowledge regarding their interactive gravity, benefiting a wide range of applications in need of prior knowledge in human spatial interactions. The ongoing COVID-19 pandemic uniquely highlights the need for monitoring and measuring fine-scale human spatial interactions. In response to the soaring needs of human mobility data under the pandemic, we developed an interactive geospatial web portal by extracting worldwide daily population flows from billions of geotagged tweets and United States (U.S.) population flows from SafeGraph mobility data. The web portal is named ODT (Origin-Destination-Time) Flow Explorer. At the core of the explorer is an ODT data cube coupled with a big data computing cluster to efficiently manage, query, and aggregate billions of OD flows at different spatial and temporal scales. Although the explorer is still in its early developing stage, the rapidly generated mobility flow data can benefit a wide range of domains that need timely access to the fine-grained human mobility records. The ODT Flow Explorer can be accessed via http://gis.cas.sc.edu/GeoAnalytics/od.html.
了解不同地点间的人类流动动态，能提供有关其交互引力的基本知识，有助于广泛应用于需要人类空间交互先验知识的领域。当前的新冠疫情凸显了监测和测量精细尺度人类空间交互的必要性。为应对疫情下对人类流动数据激增的需求，我们通过从数十亿条带有地理标记的推文提取全球每日人口流动数据，并从SafeGraph移动性数据中提取美国人口流动数据，开发了一个交互式地理空间网络门户。该网络门户名为ODT（起点 - 终点 - 时间）流量浏览器。该浏览器的核心是一个ODT数据立方体，它与一个大数据计算集群相结合，以高效管理、查询和汇总不同空间和时间尺度上的数十亿条OD流量。尽管该浏览器仍处于早期开发阶段，但快速生成的流动流量数据可惠及广泛需要及时获取细粒度人类流动记录的领域。可通过http://gis.cas.sc.edu/GeoAnalytics/od.html访问ODT流量浏览器。
