Using Ridership Profile Clustering and Geographically Weighted Regression to Investigate Spatio-Temporal Patterns of Shared E-scooter Ridership in Christchurch, New Zealand
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901620833386496 |
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| author | Leung, Wai Chi Goldie Sila-Nowicka, Katarzyna Conrow, Lindsey McKenzie, Grant Kingham, Simon da Silva Brum Bastos, Vanessa |
| author_facet | Leung, Wai Chi Goldie Sila-Nowicka, Katarzyna Conrow, Lindsey McKenzie, Grant Kingham, Simon da Silva Brum Bastos, Vanessa |
| contents | <p>This study presents the street-segment analysis of shared e-scooter ridership using real trip count data, combining Dynamic Time Warping clustering and Geographically Weighted Poisson Regression to reveal distinct patterns and spatial influencing factors of ridership in Christchurch, New Zealand.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16868798 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Using Ridership Profile Clustering and Geographically Weighted Regression to Investigate Spatio-Temporal Patterns of Shared E-scooter Ridership in Christchurch, New Zealand Leung, Wai Chi Goldie Sila-Nowicka, Katarzyna Conrow, Lindsey McKenzie, Grant Kingham, Simon da Silva Brum Bastos, Vanessa <p>This study presents the street-segment analysis of shared e-scooter ridership using real trip count data, combining Dynamic Time Warping clustering and Geographically Weighted Poisson Regression to reveal distinct patterns and spatial influencing factors of ridership in Christchurch, New Zealand.</p> |
| title | Using Ridership Profile Clustering and Geographically Weighted Regression to Investigate Spatio-Temporal Patterns of Shared E-scooter Ridership in Christchurch, New Zealand |
| url | https://doi.org/10.5281/zenodo.16868798 |