University Lecturer in Chinese Urban Development
BArch, MPhil, PhD (Cantab)
Biography:
University Lecturer in Chinese Urban Development. Dr Li Wan is interested in understanding the urban development processes, particularly those related to land use and transport, through advanced data analytics and urban system models. Prior to joining the Land Economy, he worked as a researcher at the Department of Architecture and the Centre for Smart Infrastructure and Construction at the University of Cambridge. He has been developing and applying computational models of cities and the infrastructure systems for cities in China (Beijing-Tianjin-Hebei, Guizhou, Wuhan, Chengdu), South Korea (Seoul) and UK (Cambridge), and in the process, collaborating closely with architects, urban designers, planners, engineers, economists, real estate developers and policy makers.
Dr Li Wan is accepting applications for PhD students.
Dr Li Wan is available for consultancy.
Recent Research Projects:
- Model-based Policy Study for Local Economic Development in Chengdu, China (PI, in collaboration with the Beijing Institute of Architectural Design, 2019-2020)
- A City-Level Digital Twin Experiment for Exploring the Impacts of Digital Transformation on Journeys to Work in the Cambridge Sub-region (Acting PI, funded by the Centre for Digital Built Britain, 2018-2019)
- Digital Cities for Change (Co-I, funded by The Ove Arup Foundation, 2018-2020)
- Greater Cambridge long-term economic scenario tests – model analysis for the Cambridgeshire and Peterborough Independent Economic Review (CPIER) (Modelling lead, funded by Cambridge Ahead, Cambridgeshire and Peterborough Combined Authority, 2017-2019)
- Modelling regional disparity in the UK - model analysis for the UK2070 Commission (Modelling lead, funded by the UK2070 Commission, 2019)
- Urban Modelling and Big Data Analysis for the Masterplanning of Tongzhou, Beijing (北京市通州城市副中心总体规划研究– 大数据与模型专题) (Modelling lead, funded and in collaboration with Beijing Municipal Commission of Urban Planning, 2016-2018)
Research Interests
• Urban land-use and transport
• Location and travel choices
• Inter-disciplinary modelling of urban and infrastructure systems
• Model-based development policy studies
• The integration of big data and urban system modelling
KeywordsSustainability ; Public Policy ; Economics ; Modelling |
Key Publications
An, Y.; Wan, L. (2019) Monitoring Spatial Changes in Manufacturing Firms in Seoul Metropolitan Area Using Firm Life Cycle and Locational Factors. Sustainability, 11(14), 3808; https://doi.org/10.3390/su11143808
Wan, L., Nochta, T., & Schooling, J. Developing A City-level Digital Twin - Propositions and A Case Study. International Conference on Smart Infrastructure and Construction. https://doi.org/10.17863/CAM.38703
Nochta, T., Wan, L., Schooling, J. M., Lemanski, C., Parlikad, A. K., & Jin, Y. (2019). Digitalisation for smarter cities: moving from a static to a dynamic view. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 0(0), 1–14. https://doi.org/10.1680/jsmic.19.00001
Wan, L., & Jin, Y. (2019). Assessment of model validation outcomes of a new recursive spatial equilibrium model for the Greater Beijing. Environment and Planning B: Urban Analytics and City Science, 46(5), 805–825. https://doi.org/10.1177/2399808317732575
Jin, Y., … Wan, L. et al. (2017). Environmental impacts of transformative land use and transport developments in the Greater Beijing Region: Insights from a new dynamic spatial equilibrium model. Transportation Research Part D: Transport and Environment. https://doi.org/10.1016/j.trd.2016.12.009
Wan L. et al. (2017). Big Data and Urban System Model – Substitutes or Complements? A Case Study of Modelling Commuting Patterns in Beijing. Computers, Environment and Urban Systems. https://doi.org/10.1016/j.compenvurbsys.2017.10.004
Wan L. & An Y. (2017). Identifying the Growth Patterns of High-Tech Manufacturing Industry across Seoul Metropolitan Area Using Latent Class Analysis. Journal of Urban Planning and Development, ASCE. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000397