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Our paper on Impact of weather condition on intra-urban travel behavior: evidence from taxi trajectory data has been accepted by Journal of Geo-information Science.

Abstract

Weather conditions have a substantial impact on urban residents’ daily travel activities. They usually determine the travel demand within a specific spatial location by land use type, as well as the route selection strategy between a pair of travel origin and destination. This information is crucial for stakeholders including urban dwellers, city planners and transport managers to optimize urban mobility, facility allocation and transportation resilience. In this paper, we apply spatiotemporal statistics, multiple linear regression and clustering analysis on taxi data and weather records of Wuhan City, China to understand the spatiotemporal characteristics of residents’ travel demand and taxi drivers’ route selection under different weather conditions. As a result, the dominant weather condition factors influencing residents’ travel activities are revealed on space and time. First, taxi demand is more vulnerable to weather changes on weekdays than weekends. It is negatively proportional to the increasement of rainfall, temperature and wind speed. Second, at city scale taxi demand decreases along with raining on weekdays while the demand increases on weekends. In particular, the short-distance travels increase while medium- and long-distance travels decrease. Third, taxi demand is more vulnerable to weather changes within the urban area than the suburban area. On rainy days, medium-distance travels within the urban area decrease, whereas short-distance travels within the suburban area increase. Fourth, taxi demand on residential area increases, whereas the demand on commercial area decreases on rainy days. Last, taxi drivers are found to prefer the shortest path on sunny days and the fastest path on rainy days. Those research results can assist urban planners and municipal managers to enhance their understanding of urban residents’ mobility pattern and their spatiotemporal dynamics more deeply.

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Chaogui was appointed committee member of the Chinese Society for Urban Studies from 2018 to 2023.

Abstract

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Our paper on An analytical framework for understanding urban functionality from human activities has been accepted by 10th International Conference on Geographic Information Science.

Abstract

The intertwined relationship between urban functionality and human activity has been widely recognized and quantified with the assistance of big geospatial data. In specific, urban land uses as an important facet of urban structure can be identified from spatiotemporal patterns of aggregate human activities. In this article, we propose a space, time and activity cuboid based analytical framework for clustering urban spaces into different categories of urban functionality based on the variation of activity intensity (T-fiber), mixture (A-fiber) and interaction (I- and O-fiber). The ability of the proposed framework is empirically evaluated by three case studies.

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