Spatiotemporal heterogeneity of bicycle ridership based on GTWR model.
As a low-carbon, green and environmentally friendly mode of travel, bicycles possess significant advantages in short-distance trips. In previous studies on the relationship between the built environment and bicycle behavior, the built environment variable only took into account the number or density...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0320186 |
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| author | Xiaonan Zhang Xiaohui Yan Borui Yan Shuaiyang Jiao Lei Zhang |
| author_facet | Xiaonan Zhang Xiaohui Yan Borui Yan Shuaiyang Jiao Lei Zhang |
| author_sort | Xiaonan Zhang |
| collection | DOAJ |
| description | As a low-carbon, green and environmentally friendly mode of travel, bicycles possess significant advantages in short-distance trips. In previous studies on the relationship between the built environment and bicycle behavior, the built environment variable only took into account the number or density of facilities. However, due to their different grades and formats, the attractions of similar facilities of the same size to residents vary considerably. Therefore, this paper constructs a comprehensive index of POI (Point of Interest) facility quality to reflect the influence of the number of facilities and preferences on bicycle trips. In addition, two types of riding safety indicators, namely the proportion of non-isolation bars and the proportion of non-motor vehicle lane parking, are added to the road safety facilities. On this basis, GWR and GTWR models are established to explored the temporal and spatial distribution characteristic of cycling, and identifies the relationship between cycling behavior and built environments based on 2022 Daily Trip Survey in Xianyang, China. The model results demonstrate the following: (1) The GTWR model exhibits a better fit compared to the GWR model. (2) There are significant differences between the urban central area and the marginal area, which verifies that similar facilities have diverse impacts on the cycling frequency in distinct regions. (3) The promoting or inhibiting effects of the urban built environment on the cycling frequency are highly congruent with the temporal characteristics of commuting, and these effects typically reach their maximum during commuting rush hours. (4) Cycling safety facilities constitute a significant factor influencing the cycling frequency. These results can not only offer guidance for urban planning and design but also foster the sustainable development of green transportation. |
| format | Article |
| id | doaj-art-804e7319dfb745e5bd34143c57a4bb59 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-804e7319dfb745e5bd34143c57a4bb592025-08-20T03:52:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01204e032018610.1371/journal.pone.0320186Spatiotemporal heterogeneity of bicycle ridership based on GTWR model.Xiaonan ZhangXiaohui YanBorui YanShuaiyang JiaoLei ZhangAs a low-carbon, green and environmentally friendly mode of travel, bicycles possess significant advantages in short-distance trips. In previous studies on the relationship between the built environment and bicycle behavior, the built environment variable only took into account the number or density of facilities. However, due to their different grades and formats, the attractions of similar facilities of the same size to residents vary considerably. Therefore, this paper constructs a comprehensive index of POI (Point of Interest) facility quality to reflect the influence of the number of facilities and preferences on bicycle trips. In addition, two types of riding safety indicators, namely the proportion of non-isolation bars and the proportion of non-motor vehicle lane parking, are added to the road safety facilities. On this basis, GWR and GTWR models are established to explored the temporal and spatial distribution characteristic of cycling, and identifies the relationship between cycling behavior and built environments based on 2022 Daily Trip Survey in Xianyang, China. The model results demonstrate the following: (1) The GTWR model exhibits a better fit compared to the GWR model. (2) There are significant differences between the urban central area and the marginal area, which verifies that similar facilities have diverse impacts on the cycling frequency in distinct regions. (3) The promoting or inhibiting effects of the urban built environment on the cycling frequency are highly congruent with the temporal characteristics of commuting, and these effects typically reach their maximum during commuting rush hours. (4) Cycling safety facilities constitute a significant factor influencing the cycling frequency. These results can not only offer guidance for urban planning and design but also foster the sustainable development of green transportation.https://doi.org/10.1371/journal.pone.0320186 |
| spellingShingle | Xiaonan Zhang Xiaohui Yan Borui Yan Shuaiyang Jiao Lei Zhang Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. PLoS ONE |
| title | Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. |
| title_full | Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. |
| title_fullStr | Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. |
| title_full_unstemmed | Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. |
| title_short | Spatiotemporal heterogeneity of bicycle ridership based on GTWR model. |
| title_sort | spatiotemporal heterogeneity of bicycle ridership based on gtwr model |
| url | https://doi.org/10.1371/journal.pone.0320186 |
| work_keys_str_mv | AT xiaonanzhang spatiotemporalheterogeneityofbicycleridershipbasedongtwrmodel AT xiaohuiyan spatiotemporalheterogeneityofbicycleridershipbasedongtwrmodel AT boruiyan spatiotemporalheterogeneityofbicycleridershipbasedongtwrmodel AT shuaiyangjiao spatiotemporalheterogeneityofbicycleridershipbasedongtwrmodel AT leizhang spatiotemporalheterogeneityofbicycleridershipbasedongtwrmodel |