揭示COVID-19大流行期间人类流动动态的新兴地理数据源:机遇与挑战。

IF 2.6 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computational urban science Pub Date : 2021-01-01 Epub Date: 2021-09-26 DOI:10.1007/s43762-021-00022-x
Xiao Li, Haowen Xu, Xiao Huang, Chenxiao Atlas Guo, Yuhao Kang, Xinyue Ye
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引用次数: 19

摘要

有效监测人员流动动态对城市管理非常重要,特别是在2019冠状病毒病大流行期间。传统上,人类移动数据是通过路边传感器收集的,其空间覆盖范围有限,在大规模研究中不足。随着移动传感和物联网(IoT)技术的成熟,各种众包数据源正在出现,为大流行期间监测和描述人员流动特征铺平了道路。本文就移动设备数据、社交媒体数据和网联汽车数据这三种新兴的移动数据源提出了作者的观点。我们首先介绍了每个数据源的主要特征,并总结了它们在COVID-19大流行期间跟踪流动性动态的当前应用。然后,我们讨论与使用这些数据源相关的挑战。根据作者的研究经验,我们认为数据不确定性、大数据处理问题、数据隐私和理论指导的数据分析是使用这些新兴移动数据源时最常见的挑战。最后,我们就应对这些挑战的潜在解决方案以及与获取、发现、管理和分析大移动数据相关的可能研究方向分享经验和观点。
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Emerging geo-data sources to reveal human mobility dynamics during COVID-19 pandemic: opportunities and challenges.

Effectively monitoring the dynamics of human mobility is of great importance in urban management, especially during the COVID-19 pandemic. Traditionally, the human mobility data is collected by roadside sensors, which have limited spatial coverage and are insufficient in large-scale studies. With the maturing of mobile sensing and Internet of Things (IoT) technologies, various crowdsourced data sources are emerging, paving the way for monitoring and characterizing human mobility during the pandemic. This paper presents the authors' opinions on three types of emerging mobility data sources, including mobile device data, social media data, and connected vehicle data. We first introduce each data source's main features and summarize their current applications within the context of tracking mobility dynamics during the COVID-19 pandemic. Then, we discuss the challenges associated with using these data sources. Based on the authors' research experience, we argue that data uncertainty, big data processing problems, data privacy, and theory-guided data analytics are the most common challenges in using these emerging mobility data sources. Last, we share experiences and opinions on potential solutions to address these challenges and possible research directions associated with acquiring, discovering, managing, and analyzing big mobility data.

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