Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance

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.

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

“…In general, the variation in travel volume has specificity and periodicity, which change periodically on daily and weekly bases and remain relatively stable throughout the day or week. Simultaneously public bicycles are more susceptible to weather factors because of outdoor exposure [48] Congruent with the literature [49,50], out-of-range precipitation and temperature would lead to a decline in the number of public bicycle trips and the cyclists' experience of speed…”

“…Simultaneously, public bicycles are more susceptible to weather factors because of outdoor exposure [48]. Congruent with the literature [49,50], out-of-range precipitation and temperature would lead to a decline in the number of public bicycle trips and the cyclists' experience of speed. Therefore, the calculation results of the cycling rhythm may be distorted by the of 19 amount of data and the instability of speeds.…”

Multi-Level City Portrait Research Based on Multi-Source Data

“…With the advent of the big data era, the volume of data has become richer, expanding urban research samples, and multisource data has become a mainstream trend in urban portrait research. POI data (Chen et al, 2021a), trajectory data (Park et al, 2020), and social media data (Nastar et al, 2019) and other multi-source data record multi-dimensional urban information from urban space to individual level. These data provide a novel * Corresponding author, Changfeng Jing jingcf@cugb.edu.cn way to realize three-dimensional, integrated, and multidimensional urban sensing and monitoring.…”