Toshihiro Osaragi
Biographic Data
| ID | 6311598 |
|---|---|
| NAME | Toshihiro Osaragi |
| GIVEN NAMES | Toshihiro |
| FAMILY NAME | Osaragi |
| SIGNATURE | OSARAGI T |
| AFFILIATIONS | Tokyo Institute of Technology |
| ORCID | 0000-0002-6327-3976 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
How do underground pedestrian systems in a railway transition hub area sustainably mitigate pedestrians exposure to extreme heat? A case study in Tenjin, Fukuoka, Japan
Learning Daily Human Mobility with a Transformer-Based Model
The generation and prediction of daily human mobility patterns have raised significant interest in many scientific disciplines. Using various data sources, previous studies have examined several deep learning frameworks, such as the RNN and GAN, to synthesize human movements. Transformer models have been used frequently for image analysis and language processing, while the applications of these models on human mobility are limited. In this study,…
Coastal satellite urbanization in the global south
Modelling of urban activity centers in Tokyo from alternative indicators of urban activity
Urban activity centers (UAC) – areas of the local concentrations of activities – is an effective spatial analytical tool for uncovering the spatial structure of cities. The problem is that due to the lack of the corresponding data, UAC were detected and analyzed by alternative indicators – the ones related to urban activities rather presumably than evidently. In this study, we build models allowing to predict the location of the UAC in cities bas…
Daily Human Mobility
Human movements have raised broad attention, and many models have been developed to reproduce them. However, most studies focus on reproducing the statistical properties of human mobility, such as the travel distance and the visiting frequency. In this paper, a two-step Markov Chain model is proposed to generate daily human movements, and spatial and spatiotemporal attributes of reproduced mobility are examined. In the first step, people’s status…
Why topology matters in predicting human activities
Geographic space is better understood through the topological relationship of the underlying streets (note: entire streets rather than street segments), which enables us to see scaling or fractal or living structure of far more less-connected streets than well-connected ones. It is this underlying scaling structure that makes human activities predictable, albeit in the sense of collective rather than individual human moving behavior. This topolog…
Simulating pedestrians’ spatio-temporal distribution in underground spaces
No prominent works on this page.
Why topology matters in predicting human activities
Geographic space is better understood through the topological relationship of the underlying streets (note: entire streets rather than street segments), which enables us to see scaling or fractal or living structure of far more less-connected streets than well-connected ones. It is this underlying scaling structure that makes human activities predictable, albeit in the sense of collective rather than individual human moving behavior. This topolog…
Simulating pedestrians’ spatio-temporal distribution in underground spaces
Daily Human Mobility
Human movements have raised broad attention, and many models have been developed to reproduce them. However, most studies focus on reproducing the statistical properties of human mobility, such as the travel distance and the visiting frequency. In this paper, a two-step Markov Chain model is proposed to generate daily human movements, and spatial and spatiotemporal attributes of reproduced mobility are examined. In the first step, people’s status…
Learning Daily Human Mobility with a Transformer-Based Model
The generation and prediction of daily human mobility patterns have raised significant interest in many scientific disciplines. Using various data sources, previous studies have examined several deep learning frameworks, such as the RNN and GAN, to synthesize human movements. Transformer models have been used frequently for image analysis and language processing, while the applications of these models on human mobility are limited. In this study,…
Coastal satellite urbanization in the global south
Modelling of urban activity centers in Tokyo from alternative indicators of urban activity
Urban activity centers (UAC) – areas of the local concentrations of activities – is an effective spatial analytical tool for uncovering the spatial structure of cities. The problem is that due to the lack of the corresponding data, UAC were detected and analyzed by alternative indicators – the ones related to urban activities rather presumably than evidently. In this study, we build models allowing to predict the location of the UAC in cities bas…
How do underground pedestrian systems in a railway transition hub area sustainably mitigate pedestrians exposure to extreme heat? A case study in Tenjin, Fukuoka, Japan
Human Mobility and Location-Based Analysis (4 works) · Urban Transport and Accessibility (4 works) · Computer Science (3 works) · Geography (3 works) · Artificial Intelligence (2 works) · Engineering (2 works) · Environmental planning (2 works) · Evacuation and Crowd Dynamics (2 works) · Machine learning (2 works) · Mathematics (2 works)