RESEARCH ARTICLE
Human mobility and environmental factors
Chao Li,
Alexander Ryota Keeley,
Shunsuke Managi,
Chao Li
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Search for more papers by this authorAlexander Ryota Keeley
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Search for more papers by this authorCorresponding Author
Shunsuke Managi
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Correspondence
Shunsuke Managi, Urban Institute & School of Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka City, Fukuoka 819-0395, Japan. Email: [email protected]
Search for more papers by this authorChao Li,
Alexander Ryota Keeley,
Shunsuke Managi,
Chao Li
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Search for more papers by this authorAlexander Ryota Keeley
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Search for more papers by this authorCorresponding Author
Shunsuke Managi
Urban Institute & School of Engineering, Kyushu University, Fukuoka, Japan
Correspondence
Shunsuke Managi, Urban Institute & School of Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka City, Fukuoka 819-0395, Japan. Email: [email protected]
Search for more papers by this authorFirst published: 21 April 2025
Editor Managing Review: Lynette Cheah
Abstract
Human mobility, exemplified by low-speed transportation, profoundly influences urban economics, vibrancy, and progression. With the enlarging climate change impact, a detailed exploration of the interplay between low-speed transportation and environmental elements is crucial yet seldom investigated spatially. Harnessing high-resolution origin–destination (OD) data with both spatial and temporal granularity, we construct an exceptionally precise predictive model with 88.29% accuracy. This model unravels the relationship leveraging environmental data from satellite data between January 2019 and December 2020. This study pioneers the use of Shapley additive explanation and geographically weighted panel regression to interpret extreme gradient boosting findings and spatial variability in OD data. Our analysis reveals an intriguing dichotomy: urban areas experience a decline in low-speed transportation with rising temperatures, while a positive correlation surfaces in rural regions. On average, a 1°C increase in temperature correlates to a significant reduction of 466,851 person time in low-speed transportation in Tokyo, Japan. We also identify that other environmental factors, including air pressure, wind speed, and so on, exert spatially varying impacts on low-speed transportation. Altogether, this study furnishes robust empirical evidence of the environmental effects on human mobility, presenting valuable insights for academics, policymakers, and society at large.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supporting Information
| Filename | Description |
|---|---|
| jiec70031-sup-0001-SuppMat.docx49.4 KB | Supporting Information 1: Supplementary materials to human mobility and environmental factors |
| jiec70031-sup-0002-SuppInfo.csv2.8 MB | Supporting Information 2: Data Supports Figure 6 |
| jiec70031-sup-0003-SuppInfo.csv7.5 MB | Supporting Information 3: Data Supports Figure 7 |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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