Understanding Shared Micromobility in China Using Massive User-Generated Trip Data

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Éditeur :

Springer

Paru le : 2025-09-26

This book provides a data-driven analysis of shared micromobility in China. Both bike-sharing and e-bike-sharing are considered and several Chinese cities (e.g., Shanghai and Hangzhou) are selected as study cases. It adopts a variety of methods including GIS, big data analytics, social network analy...
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Éditeur

Collection
n.c

Parution
2025-09-26

Pages
193 pages

EAN papier
9789819684915

Auteur(s) du livre


Yongping Zhang is a tenure-track assistant professor at the School of Public Affairs, Zhejiang University, China. He also serves as the deputy director of the ZJU-CMZJ Joint Lab on Data Intelligence and Urban Future, the director of the City+ Research Network, and the editorial board member of the Journal of Transport Geography. He has a research interest in urban big data analysis, smart cities, digital urban governance, sustainable transport and GIS, with a focus on understanding various urban issues by emerging quantitative methods and urban data sources. At present, he has published more than 40 peer-reviewed papers in international journals such as Applied Energy, Cities, Environment and Planning B, Journal of Transport Geography, and Sustainable Cities and Society. He received his PhD degree in Advanced Spatial Analysis from University College London (the UK). Before this, he obtained three master degrees: one in European Spatial Planning and Environmental Policy from Cardiff University (the UK), one in Environment and Society Studies from Radboud University Nijmegen (the Netherlands), and one in Urban and Regional Planning from Peking University (China). He obtained his bachelor degree in Geographic Information System (GIS) from Wuhan University (China).

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EAN PDF
9789819684922
Prix
105,49 €
Nombre pages copiables
1
Nombre pages imprimables
19
Taille du fichier
21135 Ko
EAN EPUB
9789819684922
Prix
105,49 €
Nombre pages copiables
1
Nombre pages imprimables
19
Taille du fichier
71291 Ko

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