Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance
Abstract
:1. Introduction
2. Literature Review
2.1. Impact of Weather Elements on Travel Choices
2.2. Impact of Extreme Climate Events on Travel Choices
3. Study Area and Data Description
3.1. Study Area
3.2. Data Description
4. Methodology
4.1. Inference Method for Impact of Public Bicycle Trips
4.2. Place semantic Recognition and Weighted Method
4.3. Riding Distance Analysis and Statistics Method
5. Analysis Results
5.1. Spatial Difference of Reduced Public Bicycle Trips during the PRS
5.2. Spatial Distribution of Affected Level
5.2.1. Affected Level Analysis Based on the Number of Cyclists
5.2.2. Affected Level Analysis Based on Place Semantic
5.2.3. Affected Level Analysis Based on Riding Distance
5.3. Spatial Pattern of Multivariate Impact by Plum Rain
6. Discussion and Conclusions
6.1. Discussion
6.1.1. Unfixed Rainy Days and Interannual Variability of the PRS
6.1.2. Perspectives Selection of Affected Dimensions
6.2. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Liu, C.; Susilo, Y.O.; Karlström, A. The influence of weather characteristics variability on individual’s travel mode choice in different seasons and regions in Sweden. Transp. Policy 2015, 41, 147–158. [Google Scholar] [CrossRef]
- Liu, C.; Susilo, Y.O.; Karlström, A. Investigating the impacts of weather variability on individual’s daily activity–travel patterns: A comparison between commuters and non-commuters in Sweden. Transp. Res. Part A Policy Pract. 2015, 82, 47–64. [Google Scholar] [CrossRef]
- Abkowitz, M.; Jones, A.; Dundon, L.; Camp, J. Performing a regional transportation asset extreme weather vulnerability assessment. Transp. Res. Procedia 2017, 25, 4422–4437. [Google Scholar] [CrossRef]
- Zanni, A.M.; Ryley, T.J. The impact of extreme weather conditions on long distance travel behaviour. Transp. Res. Part A Policy Pract. 2015, 77, 305–319. [Google Scholar] [CrossRef]
- Guanying, Y.; Yihan, H.; Yang, G.; Huang, Y.; Liu, M.; Wang, X.; Yixing, Y.; Cui, H.; Xiaojun, W. Changes in the summer extreme precipitation in the Jianghuai plum rain area and their relationship with the intensity anomalies of the south Asian high. Atmos. Res. 2019, 236, 104793. [Google Scholar] [CrossRef]
- Zhou, L.; Ye, B.; Xia, S. Assessing membrane biofouling and its gel layer of anoxic/oxic membrane bioreactor for megacity municipal wastewater treatment during plum rain season in Yangtze River Delta, China. Water Res. 2017, 127, 22–31. [Google Scholar] [CrossRef] [PubMed]
- Nankervis, M. The effect of weather and climate on bicycle commuting. Transp. Res. Part A Policy Pract. 1999, 33, 417–431. [Google Scholar] [CrossRef]
- Arana, P.; Cabezudo, S.; Peñalba, M. Influence of weather conditions on transit ridership: A statistical study using data from Smartcards. Transp. Res. Part A Policy Pract. 2014, 59, 1–12. [Google Scholar] [CrossRef]
- Böcker, L.; Dijst, M.; Faber, J. Weather, transport mode choices and emotional travel experiences. Transp. Res. Part A Policy Pract. 2016, 94, 360–373. [Google Scholar] [CrossRef]
- Singhal, A.; Kamga, C.; Yazici, A. Impact of weather on urban transit ridership. Transp. Res. Part A Policy Pract. 2014, 69, 379–391. [Google Scholar] [CrossRef]
- Soni, A.R.; Chandel, M.K. Impact of rainfall on travel time and fuel usage for Greater Mumbai city. Transp. Res. Procedia 2020, 48, 2096–2107. [Google Scholar] [CrossRef]
- Wang Yuan-Qing, L.J. Study of Rainfall Impacts on Freeway Traffic Flow Characteristics. Transp. Res. Procedia 2016, 25, 1533–1543. [Google Scholar] [CrossRef]
- Liu, K.; Wang, M.; Cao, Y.; Zhu, W.; Yang, G. Susceptibility of existing and planned Chinese railway system subjected to rainfall-induced multi-hazards. Transp. Res. Part A Policy Pract. 2018, 117, 214–226. [Google Scholar] [CrossRef]
- Dijst, M.; Böcker, L.; Kwan, M.-P. Exposure to weather and implications for travel behaviour: Introducing empirical evidence from Europe and Canada. J. Transp. Geogr. 2013, 28, 164–166. [Google Scholar] [CrossRef]
- Zhou, M.; Wang, D.; Li, Q.; Yue, Y.; Tu, W.; Cao, R. Impacts of weather on public transport ridership: Results from mining data from different sources. Transp. Res. Part C Emerg. Technol. 2017, 75, 17–29. [Google Scholar] [CrossRef] [Green Version]
- Wadud, Z. Cycling in a changed climate. J. Transp. Geogr. 2014, 35, 12–20. [Google Scholar] [CrossRef] [Green Version]
- Wu, J.; Liao, H. Weather, travel mode choice, and impacts on subway ridership in Beijing. Transp. Res. Part A Policy Pract. 2020, 135, 264–279. [Google Scholar] [CrossRef]
- Wei, M.; Liu, Y.; Sigler, T.; Liu, X.; Corcoran, J. The influence of weather conditions on adult transit ridership in the sub-tropics. Transp. Res. Part A Policy Pract. 2019, 125, 106–118. [Google Scholar] [CrossRef]
- El-Assi, W.; Mahmoud, M.S.; Habib, K.N. Effects of built environment and weather on bike sharing demand: A station level analysis of commercial bike sharing in Toronto. Transportation 2017, 44, 589–613. [Google Scholar] [CrossRef]
- Maas, S.; Attard, M.; Caruana, M.A. Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria. Transp. Res. Part A Policy Pract. 2020, 140, 81–97. [Google Scholar] [CrossRef]
- Morton, C. The demand for cycle sharing: Examining the links between weather conditions, air quality levels, and cycling demand for regular and casual users. J. Transp. Geogr. 2020, 88, 102854. [Google Scholar] [CrossRef]
- Nosal, T.; Miranda-Moreno, L.F. The effect of weather on the use of North American bicycle facilities: A multi-city analysis using automatic counts. Transp. Res. Part A Policy Pract. 2014, 66, 213–225. [Google Scholar] [CrossRef]
- Motoaki, Y.; Daziano, R.A. A hybrid-choice latent-class model for the analysis of the effects of weather on cycling demand. Transp. Res. Part A Policy Pract. 2015, 75, 217–230. [Google Scholar] [CrossRef]
- Helbich, M.; Böcker, L.; Dijst, M. Geographic heterogeneity in cycling under various weather conditions: Evidence from Greater Rotterdam. J. Transp. Geogr. 2014, 38, 38–47. [Google Scholar] [CrossRef]
- Lu, Q.-C.; Zhang, J.; Peng, Z.-R.; Rahman, A.S. Inter-city travel behaviour adaptation to extreme weather events. J. Transp. Geogr. 2014, 41, 148–153. [Google Scholar] [CrossRef]
- Zheng, M.-C.; Liu, Y.-W. Effect of Compositions of MRT System Route Maps on Cognitive Mapping. ISPRS Int. J. Geo Inf. 2021, 10, 569. [Google Scholar] [CrossRef]
- Li, P.; Abdel-Aty, M.; Yuan, J. Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data. Accid. Anal. Prev. 2021, 150, 105924. [Google Scholar] [CrossRef] [PubMed]
- Scarchilli, C.; Frezzotti, M.; Grigioni, P.; De Silvestri, L.; Agnoletto, L.; Dolci, S. Extraordinary blowing snow transport events in East Antarctica. Clim. Dyn. 2009, 34, 1195–1206. [Google Scholar] [CrossRef] [Green Version]
- Ngo, N.S. Urban bus ridership, income, and extreme weather events. Transp. Res. Part D Transp. Environ. 2019, 77, 464–475. [Google Scholar] [CrossRef]
- Jain, D.; Singh, S. Adaptation of trips by metro rail users at two stations in extreme weather conditions: Delhi. Urban Clim. 2021, 36, 100766. [Google Scholar] [CrossRef]
- Miao, Q.; Feeney, M.K.; Zhang, F.; Welch, E.W.; Sriraj, P. Through the storm: Transit agency management in response to climate change. Transp. Res. Part D Transp. Environ. 2018, 63, 421–432. [Google Scholar] [CrossRef]
- Kamga, C.; Yazıcı, M.A. Temporal and weather related variation patterns of urban travel time: Considerations and caveats for value of travel time, value of variability, and mode choice studies. Transp. Res. Part C Emerg. Technol. 2014, 45, 4–16. [Google Scholar] [CrossRef]
- Khattak, A.; De Palma, A. The impact of adverse weather conditions on the propensity to change travel decisions: A survey of Brussels commuters. Transp. Res. Part A Policy Pract. 1997, 31, 181–203. [Google Scholar] [CrossRef]
- Guo, Z.; Wilson, N.H.M.; Rahbee, A. Impact of Weather on Transit Ridership in Chicago, Illinois. Transp. Res. Rec. J. Transp. Res. Board 2007, 2034, 3–10. [Google Scholar] [CrossRef]
- Zhang, L.; Traore, S.; Ge, J.; Li, Y.; Wang, S.; Zhu, G.; Cui, Y.; Fipps, G. Using boosted tree regression and artificial neural networks to forecast upland rice yield under climate change in Sahel. Comput. Electron. Agric. 2019, 166, 105031. [Google Scholar] [CrossRef]
- Hyndman, R.; Khandakar, Y. Automatic Time Series Forecasting: The forecast package for R. J. Stat. Softw. 2008, 27, 1–22. [Google Scholar] [CrossRef] [Green Version]
- Elgindy, E.; Abdelmoty, A. Capturing Place Semantics on the Geo Social Web. J. Data Semant. 2014, 3, 207–223. [Google Scholar] [CrossRef] [Green Version]
- Aitken, S.C.; Prosser, R. Residents’ Spatial knowledge of neighborhood continuity and form. Geogr. Anal. 2010, 22, 301–325. [Google Scholar] [CrossRef]
- Root, E.D. Moving neighborhoods and health research forward: Using geographic methods to examine the role of spatial scale in neighborhood effects on health. Ann. Assoc. Am. Geogr. 2012, 102, 986–995. [Google Scholar] [CrossRef] [Green Version]
- ElGindy, E.; Abdelmoty, A. Enriching user profiles using geo-social place semantics in geo-folksonomies. Int. J. Geogr. Inf. Sci. 2014, 28, 1439–1458. [Google Scholar] [CrossRef] [Green Version]
- Chen, L.; Moore, A.; Mandic, S. Using exploratory spatial analysis to understand the patterns of adolescents’ active transport to school and contributory factors. ISPRS Int. J. Geo Inf. 2021, 10, 495. [Google Scholar] [CrossRef]
- Böcker, L.; Thorsson, S. Integrated weather effects on cycling shares, frequencies, and durations in Rotterdam, The Netherlands. Weather. Clim. Soc. 2014, 6, 468–481. [Google Scholar] [CrossRef]
- Zhao, J.; Wang, J.; Xing, Z.; Luan, X.; Jiang, Y. Weather and cycling: Mining big data to have an in-depth understanding of the association of weather variability with cycling on an off-road trail and an on-road bike lane. Transp. Res. Part A Policy Pract. 2018, 111, 119–135. [Google Scholar] [CrossRef]
- Pröbstl-Haider, U.; Hödl, C.; Ginner, K.; Borgwardt, F. Climate change: Impacts on outdoor activities in the summer and shoulder seasons. J. Outdoor Recreat. Tour. 2021, 34, 100344. [Google Scholar] [CrossRef]
- Schimohr, K.; Scheiner, J. Spatial and temporal analysis of bike-sharing use in Cologne taking into account a public transit disruption. J. Transp. Geogr. 2021, 92, 103017. [Google Scholar] [CrossRef]
Statistical Characteristic | Workday (Predicted Value) | Workday (Observed Value) | Weekend (Predicted Value) | Weekend (Observed Value) |
---|---|---|---|---|
Total number of trips | 106,690 | 50,283 | 98,877 | 34,071 |
standard deviation | 85.31 | 42.94 | 84.47 | 33.00 |
clustering coefficient | 38.17 | 36.17 | 40.62 | 41.39 |
Pattern Name | Proportion | Description of Pattern | ||
---|---|---|---|---|
Riding Distance-Based Impact | Place Semantic- Based Impact | Cyclists Number-Based Impact | ||
Pattern I | 29.87% | Moderate | High | Low |
Pattern II | 26.21% | Moderate | Low | Low |
Pattern III | 18.40% | Moderate | High | Higher |
Pattern IV | 4.45% | High | Moderate | Higher |
Pattern V | 7.12% | Higher | High | High |
Pattern VI | 11.47% | Moderate | Low | Higher |
Pattern VII | 2.47% | Higher | Moderate | Moderate |
Pattern Name | Proportion | Description of Pattern | ||
---|---|---|---|---|
Riding Distance-Based Impact | Place Semantic- Based Impact | Cyclists Number-Based Impact | ||
Pattern I | 19.56% | Moderate | High | Low |
Pattern II | 15.27% | Moderate | Low | Higher |
Pattern III | 16.07% | Moderate | High | Higher |
Pattern IV | 1.70% | High | Moderate | Moderate |
Pattern V | 36.23% | Moderate | Low | Low |
Pattern VI | 4.19% | Higher | High | Higher |
Pattern VII | 6.99% | Higher | Moderate | Moderate |
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Chen, L.; Zhang, H.; Wang, H.; Wu, P. Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance. ISPRS Int. J. Geo-Inf. 2021, 10, 695. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100695
Chen L, Zhang H, Wang H, Wu P. Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance. ISPRS International Journal of Geo-Information. 2021; 10(10):695. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100695
Chicago/Turabian StyleChen, Lijun, Haiping Zhang, Haoran Wang, and Peng Wu. 2021. "Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance" ISPRS International Journal of Geo-Information 10, no. 10: 695. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100695