Abstract
The effect of the plum rain weather event on cycling trips reflects the climate resilience of the public bicycle system. However, quantitative studies regarding the impact of plum rain on public bicycle users and corresponding spatial heterogeneity have not been paid much attention. This paper explores the spatial pattern of affected levels from the perspective of cyclist number, place semantics and riding distance. Corresponding public bicycle trips in normal weather are predicted by spatial-temporal random forest prediction. GIS neighborhood statistics and clustering algorithms are adapted to analyze and visualize the affected levels using origin-destination data of public bicycle trips and point of interest data of city public facilities. It is proved that there is an obvious spatial difference in affected levels by plum rain from three dimensions. In the dimension of the number of cyclists, the docking stations with different affected levels are distributed across the whole urban area. In the place semantic dimension, the docking stations with high affected levels show a clustered zonal distribution in the city center. In the dimension of cycling distance, the docking stations with high affected levels are mainly distributed in the periphery of the central urban area. The study theoretically expands the impact mechanism of environment and active transport. It is beneficial for the early monitoring, warning and assessment of climate change risks for public bicycle planning and management.
Highlights
Climate and environmental problems are challenges for human beings
This study shows a very obvious decline in public bicycle trips during the plum rainy season (PRS), which reduced by 52.86% on workdays and
The semantic difference in the reduced amount of public bicycle trips is obvious during the PRS
Summary
Climate and environmental problems are challenges for human beings. Climatic conditions undoubtedly have an obvious impact on people’s daily travelling behavior [1,2].Extreme climate events [3,4], such as heavy snow, fog, freezing, intense hurricanes, strong wind, high/low temperature, heavy rain, continuous rain, and rising sea levels, can greatly increase the vulnerability of the transportation system. Climate and environmental problems are challenges for human beings. Climatic conditions undoubtedly have an obvious impact on people’s daily travelling behavior [1,2]. Extreme climate events [3,4], such as heavy snow, fog, freezing, intense hurricanes, strong wind, high/low temperature, heavy rain, continuous rain, and rising sea levels, can greatly increase the vulnerability of the transportation system. Different kinds of climatic scenarios and different transit modes result in different responses from transportation sectors and people. Analyzing and studying the influence of weather on residents’ transit modes are of great significance in deeply understanding the cognition of the transportation environment. This study will provide guidance to management authorities on coping with the effects of extreme weather events on the transportation system
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