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Urban Informatics and Future CitiesDevelopment of a Spatio-Temporal Analysis Method to Support the Prevention of COVID-19 Infection: Space-Time Kernel Density Estimation Using GPS Location History Data

Urban Informatics and Future Cities: Development of a Spatio-Temporal Analysis Method to Support... [This study aims to develop a spatio-temporal analysis method to support planning for the prevention of a COVID-19 infection. The method focused on the space-time kernel density estimation using the GPS location history data. The data is GPS location data obtained at regular intervals from smartphones with the consent of the users. The research method was a panel data analysis for April 2019 and April 2020 with Ibaraki City. In April 2020, the Japanese government implemented a soft lockdown. As a result, this study developed a spatio-temporal analysis method that visualizes the space-time with high population density. Using these methods, local governments can restrict people’s lives by designating specific space-time areas. In addition, the method helps citizens to change their lifestyle behaviors and cooperate in the prevention of COVID-19 infection. The method is an alternative to the Japanese soft lockdown, which was based on an emergency declaration. In the future, this method will be utilized for data analysis in future smart cities.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Urban Informatics and Future CitiesDevelopment of a Spatio-Temporal Analysis Method to Support the Prevention of COVID-19 Infection: Space-Time Kernel Density Estimation Using GPS Location History Data

Part of the The Urban Book Series Book Series
Editors: Geertman, S. C. M.; Pettit, Christopher; Goodspeed, Robert; Staffans, Aija
Kato, Haruka
Urban Informatics and Future Cities — Jul 16, 2021
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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
ISBN
978-3-030-76058-8
Pages
51 –67
DOI
10.1007/978-3-030-76059-5_4
Publisher site
See Chapter on Publisher Site

Abstract

[This study aims to develop a spatio-temporal analysis method to support planning for the prevention of a COVID-19 infection. The method focused on the space-time kernel density estimation using the GPS location history data. The data is GPS location data obtained at regular intervals from smartphones with the consent of the users. The research method was a panel data analysis for April 2019 and April 2020 with Ibaraki City. In April 2020, the Japanese government implemented a soft lockdown. As a result, this study developed a spatio-temporal analysis method that visualizes the space-time with high population density. Using these methods, local governments can restrict people’s lives by designating specific space-time areas. In addition, the method helps citizens to change their lifestyle behaviors and cooperate in the prevention of COVID-19 infection. The method is an alternative to the Japanese soft lockdown, which was based on an emergency declaration. In the future, this method will be utilized for data analysis in future smart cities.]

Published: Jul 16, 2021

Keywords: Spatio-temporal analysis method; COVID-19; Space-time kernel density estimation; GPS location history data; Smartphone GPS data

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