We are a modelling research group focusing on understanding urban land and transport development processes and policy mechanisms through applied urban modelling and data analytics.
The research group is led by Dr Li WAN.
Dr. Li Wan
The future of work is rapidly changing – home and hybrid working arrangements will have profound impact on urban life beyond the pandemic. Applying Latent Class Analysis to a novel repeated cross-sectional Time Use Survey dataset in the UK, distinct lifestyles are identified according to working arrangement and daily time utilisation patterns. Qualitative pen portraits are assigned to each lifestyle and their sociodemographic characteristics are analysed. COVID impacts on subjective wellbeing for the differentiated lifestyles are quantified with regard to activity composition and duration. Policy implications of promoting lifestyle flexibility are formulated and discussed along the spatial and temporal dimensions.
This research switches the policy assessment from the single city and one policy analysis into a multi-policy city-regional scale assessment by considering the city network, different hierarchical city levels, and policy scenario comparison. The changing preferences for city-center and suburban amenities and the popularity of remote work in the post-pandemic are two new challenges to existing SCGE models. Those two new challenges on existing SCGE models have been considered in this research to model the public location choice and urban spatial structure.
This study builds on the activity-based approach in transport modelling and expands it as a unified analytical framework for quantifying the effects of the land-use and transport planning on long-term city-scale energy intensity in fast-growing city regions. The new modelling framework features a consistent activity-based choice model linking the building and transport sector, subject to explicit time and budget constraints and spatial equilibrium condition in the housing market. The study demonstrates the policy use of the model through an empirical model application for the Greater Beijing in China and estimates the carbon/energy intensity elasticities with respect to planning policy variables with the base-year model after calibration. The calibrated model will then be used to estimate the emission/energy outlook based on a series of urban spatial development scenarios and to test the magnitude and rate of technological and behavioural change required for achieving local sustainability goals.
The study aims to quantitatively assess the spatial and economic impact of Ethnic Integration Policy (EIP) on the development of housing market and urban spatial structure in Singapore. Specifically, two main research questions are proposed. (1) Whether EIP would have an impact on the spatial pattern and time-series changes of housing price in Singapore? If so, how would EIP affect the development of urban spatial structure in Singapore through its impact on the housing market? (2) How to mitigate/enhance the negative/positive impact of EIP in relation to the 2030 planning goals in Singapore? The research design includes three main work packages, population synthesis, modelling residential location choice under housing market equilibrium and policy scenario analysis.
The theoretical interaction between land-use and urban infrastructure is articulate in literature, but the coordination of the two policy domains remains a challenging task in planning practice. The fast urbanisation in Chinese cities features a distinct land finance model, where land supply, employment growth, government revenue and infrastructure investment constitute a complex nexus of interdependences. This research aims to address this gap by quantifying the potential causal relationships between land-use planning, employment and urban infrastructure service mediated by two main government revenue accounts for over 200 prefecture-level cities in mainland China. By incorporating latent classes of cities in a series of structural equation models (SEM), this research confirms that 1) land-use planning is a significant variable that affects the development of urban infrastructure services through land finance, and 2) there is significant cross-city heterogeneity on the role of land-use planning in influencing employment and infrastructure growth. This study provides new policy insights on the varying efficiency of land use across cities.
Night-time light (NTL) data provide a novel and accessible source for monitoring the Spatio-temporal dynamics of urban expansion. The static thresholds ignore the path-dependent nature of urban development. Using NTL data for 2012-2018, this study proposes a new method using dynamic threshold (DT) for extracting UBA using NTL data for 600+ Chinese cities. The dynamic thresholds explicitly address the temporal continuity of urban physical development and further consider intra-city heterogeneity in terms of NTL brightness change pattern. Through a comparison with official statistics in China and UN-Habitat Sentinel-2 Human Settlement data, it is demonstrated that the overall accuracy of the DT method exceeds 85%, and the Kappa index exceeds 0.45.
Published on Travel Behaviour and Society, 2021
Published on Transport Policy, 2021
Published on Computers, Environment and Urban Systems, 2017
Presentation for the Data for Policy 2021 Conference, 2021
Published on Journal of Urban Technology, 2020
Published on ISPRS International Journal of Geo-Information, 2020
Published on International Conference on Smart Infrastructure and Construction, 2019
Financial Times article, 2020
Published on Landscape Architecture Frontiers, 2019
Published on Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 2019
Published on Environment and Planning B: Urban Analytics and City Science, 2019
Published on Transportation Research Part D: Transport and Environment, 2017
For the UK2070 Commission, 2020
Published on Sustainability, 2019
Published on Journal of Urban Planning and Development, ASCE, 2017
This paper studies the spatial impact of COVID-19 pandemic through the lens of intra-city population and house rent changes in Beijing, China. Drawing on multiple geospatial data sets, we find that the pandemic has flattened the housing bid-rent curve in Beijing, which corroborates existing literature mainly based on cities in developed countries. Through regression analysis and spatial equilibrium modelling, we identify key mechanisms of the flattened bid-rent curve and the accompanying decentralisation of residents. First, workplace population change, particularly in central Beijing, seems to be the main factor contributing to the resident population and house rent changes. Second, we find no significant evidence on the spatial impact from remote working, as the share of remote working in Beijing appears low after about one year recovery. This finding contrasts to existing studies where remote working has been perceived as the main driver for urban spatial structure change in a developed country context. Third, through a novel method for quantifying locational preference changes, it is found that the observed decentralisation trend in Beijing, ceteris paribus, may also be associated with increased (decreased) preference for living in suburban (central) locations. However, the preference change for central locations is marginal, hence providing an early rebuttal of the ‘demise of centres’ proposition.https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3908277
The rapid urbanisation in Chinese cities features a distinctive land finance model, where land market, local economy, government revenue, and urban development are intertwined. Quantifying the interdependence between land market and other parts of the social, economic, and political systems has been a challenging undertaking, and the task is further complicated by the great cross-city heterogeneity in natural endowment and local socio-economic conditions. Few existing studies succeeded in capturing both the complexity of the system and the nuance of cross-city variations at the same time. We propose a novel structural equation modelling (SEM) method, integrated with the latent class analysis (LCA), to address this challenge. The LCA is used to identify distinct city groups based on two purposely constructed land-use efficiency measurements. The categorical latent classes of cities are then incorporated in a series of structural equation models, capturing the non-linear heterogeneity across cities. Based on data for 272 prefecture-level Chinese cities between 2012 and 2017, we found quantified evidence on both the direct channel (i.e., one-off revenue from land conveyance fee) and indirect channel (e.g., sustainable tax revenue from the business and employment growth enabled by land development) through which land supply drives urban development. The study also quantifies the significant gap among Chinese cities in terms of land-use efficiency. Our findings highlight the importance of developing and implementing reliable land-use efficiency measurements, the need to shift policy focus from one-off income to long-term sustainable revenue, and the potential of lower-tier cities in the next stage of urbanisation in China.https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3973056
Mental health in the UK had deteriorated compared with pre-pandemic trends. The impact of COVID-19 on the subjective wellbeing of working populations with distinct lifestyles is not yet studied. Methods: Combining time use surveys collected pre- and during COVID-19, latent class analysis was used to identify distinct lifestyles based on aggregated daily activity patterns and reported working modes. We provide qualitative pen portraits alongside pre-versus-during pandemic comparisons of intraday time use and wellbeing patterns. Lifestyle heterogeneity in wellbeing was quantified in relation to aggregated activity types. Results: COVID-19 impact on wellbeing varied significantly between usual working hours (6am-6pm) and rest of the day. The decline in wellbeing outside of usual working hours was significant and consistent across lifestyles. During usual working hours, the direction of impact varied in line with working modes: wellbeing of homeworkers decreased, remained relatively stable for commuters, and increased for certain hybrid workers. Magnitude of impact correlates strongly with lifestyle: those working long and dispersed hours are more sensitive, whereas non-work dominated lifestyles are more resilient. Conclusion: The direction and magnitude of impact from COVID-19 were not uniformly manifested across activity types, time of day, and latent lifestyles. Blurring work-life boundaries and general anxiety about the pandemic may be key determinants of the decline outside of usual working hours. During usual working hours, strong yet complex correlations between wellbeing and time-use changes suggested that policies aiming to enhance wellbeing of workers need to consider not only spatial flexibility but also provide wider support for temporal flexibility.https://www.medrxiv.org/content/10.1101/2022.04.27.22273297v1
Earlier this month, the UK Government unveiled an overdue yet ambitious 'levelling-up’ plan that aims to spread opportunity and prosperity to all parts of the UK. A quick word search through the Executive Summary reveals that the word ‘planning’ appears only twice, one referring to the protection of Green Belts and another alluding to the seemingly stalled planning reform...    [Read more]
A new method for identifying built-up areas using night-time light data – A case study of 600+ Chinese cities
Further information can be found at:https://www.polyu.edu.hk/lsgi/news-and-events/events/2022/1/0128_liwan/