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.
Recent Book: Digital Twins for Smart Cities: Conceptualisation, challenges and practices.
Dr. Li Wan
Dr. Jerry Chen
Dr. Yu Han
Ilaï Bendavid
Qiancheng Wang
Yibin Li
Shantong Wang
Emily Tianyuan Wang
Causality between the built environment and subjective wellbeing has thus far been segmentally explored and partially quantified. We identify two unresolved challenges in the literature. Firstly, a reliance on cross-sectional data produces associative findings. Secondly, a reductive approach to regress aggregate subjective wellbeing on limited and disparate built environment measurements risks significant confounding effects. We address the research gaps by leveraging residential relocation as a natural experiment to investigate the causality between built environment change and subjective wellbeing. Two causal inference methods (difference-in-differences and synthetic control) are applied and compared. Our research design incorporates novel extensions to the canonical forms of both causal inference methods – staggered difference-in-differences and generalised synthetic control methods – to accommodate individual-level data with multiple relocation timepoints.
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.
Inter-city development disparity is a salient issue for both developed and developing countries. A causal determination of whether and to what extent variations in planning policies lead to different outcomes remains an onerous analytical challenge. Quantitative modelling of such causality requires the identification of a bundle of planning strategies from text-based planning documents in a holistic and temporally consistent manner such that the evolution of development outcomes could be investigated in relation to planning policy changes over time. Enabled by recent progress in natural language processing (NLP), this paper presents a novel NLP application for identifying key planning strategies from a large amount of text-based government documents through a case study of 117 prefecture-level cities in China. Based on official, city-level government reports from 2011 to 2019, the evolving policy strategies are identified and linked with the change of development outcome. Policy implications and directions for future research are discussed.
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.
The Charging Infrastructure (CI) enables large uptakes of Electric Vehicle (EV) for transport decarbonisation. However, the large adoption of EVs may cause congestions. For sustainable mobility, it is timely important to incorporate congestion control when promoting EVs. Smart placement and operation of CIs should be applied to tackle congestion issues by proactively intervening traffic and driving behaviours for the more EV transport system. CI planning should be considered with the public transport while car dependency can be influenced by economic factors such as charging prices. The research question is how adaptive and inter-sectoral EV charging policies may help mitigate car dependence and complement public transport by spatial and technical configuration of CIs and the associated pricing mechanism. Parameters of traffic, parking, demography and public transport will be incorporated with spatial analysis, while the feasibility of employing dynamic and adaptive charging pricing to influence travel behaviour will be explored.
The growing penetration of ICT has redefined recreational activities and changed the demand, choice, and location of urban recreational services. As the Chinese proverb goes, “fragrant wine would not be restricted by deep alleys,” ICT has alleviated many restrictions imposed by conventional locations on people’s spatial preference for leisure activities, enabling new forms and levels of functional integration. Under the influence of ICT, urban recreational service space has been spreading to the urban suburbs and further penetrating the urban two-dimensional and three-dimensional spaces such as residential and office areas. In this context, urban mixed-use development evolves from block scale to the building scale and from ground level to ground above level, resulting in the need for new policies and regulations. Therefore, this study aims to measure the penetration degree of recreational service, identify the characteristics of the built environment elements, and explore urban planning and real estate policy by referring to international case studies. The findings could enhance the theory of mixed-use development and compact city in the digital era, and contribute to policymaking for managing and re-purposing urban spaces, especially for high-density cities.
Published on Environment and Planning B: Urban Analytics and City Science, 2024
Digital Twins for Smart Cities: Conceptualisation, challenges and practices，2023
Digital Twins for Smart Cities: Conceptualisation, challenges and practices，2023
Published on ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences，2022
Digital Twins in the Built Environment: Fundamentals, principles and applications，2022
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
Financial Times article, 2020
Published on International Conference on Smart Infrastructure and Construction, 2019
Routledge Handbook of Smart Built Environment, 2025
IET Smart Cities, 2023
Published on Journal of Urban Management, 2023
Published online by Cambridge University Press, 2023
Published on Cities, 2022
Published on Landscape Architecture Frontiers, 2020
Published on Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 2019
Published on International Journal of Urban Sciences, 2025
Published on Transportation Research Part D: Transport and Environment, 2024
Published on Plos One, 2024
Published on International Journal of Sustainable Transportation, 2023
Published on Travel Behaviour and Society, 2021
Published on Transport Policy, 2021
Published on Computers, Environment and Urban Systems, 2017
Lincoln Institute Working Paper, 2022
For the UK2070 Commission, 2020
Published on Environment and Planning B: Urban Analytics and City Science, 2019
Published on Transportation Research Part D: Transport and Environment, 2017
Published on Cambridge Journal of Regions, Economy and Society, 2022
Published on Sustainability, 2019
Published on Journal of Urban Planning and Development, ASCE, 2017
The growing prevalence of flexible/remote working and the policy push for active travel since the COVID-19 pandemic are expected to help to mitigate urban traffic congestion. However, despite a marked decline in overall travel demand in Great Britain, some cities are experiencing unabated, if not worsened, traffic congestion. This study aims to investigate this paradox of post-pandemic travel through an in-depth case study of Cambridge, a city with a high proportion of high-skilled professional employment in the UK. Using longitudinal traffic count and car journey time data, we compare intra-day and intra-week travel demand patterns across four distinct periods, namely the pre-pandemic, during pandemic, post-pandemic transitional and post-pandemic stabilised periods, controlling for month, school and university term, bank holidays, major public events, roadworks, traffic accidents and weather. It is shown that recent car and cycle demand in Cambridge remains at 11.6% and 15.8% below pre-pandemic levels, respectively, and has stabilised since 2022. Despite the overall reduction in travel demand, daily average journey time on key transport corridors in Cambridge has increased by 12.0% from 2022 to 2024. The rise in journey time is particularly salient at evening peaks and on Thursdays, with the former being the primary factor. The increase in peak-time journey time in Cambridge is likely to be caused by supply-side factors. Important policy implications are drawn.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4970168Causality between the built environment and subjective wellbeing has thus far been segmentally explored and partially quantified. We identify two unresolved challenges in the literature. Firstly, a reliance on cross-sectional data produces associative findings. Secondly, a reductive approach to regress aggregate subjective wellbeing on limited and disparate built environment measurements risks significant confounding effects. We address the research gaps by leveraging residential relocation as a natural experiment to investigate the causality between built environment change and subjective wellbeing (measured with composite score of negatively phrased General Health Questionnaire-12 items). Two causal inference methods (difference-in-differences and synthetic control) are applied and compared. The use of the ‘Understanding Society’ dataset (The UK Household Longitudinal Study, 2009-2019), combined with holistic locational attributes (Area Classification at the Lower Super Output Area level as per the UK Census) for exploring such causality is novel in literature. Specifically, to estimate the wellbeing effects of residential relocation, we compare movers (treatment n=773) to non-movers (control n=4,619). To estimate the effects of built environment change, we compare movers with a change of built environment type (n=506) to those moving into the same built environment type (n=267). Our research design incorporates novel extensions to the canonical forms of both causal inference methods – staggered difference-in-differences and generalised synthetic control methods – to accommodate individual-level data with multiple relocation timepoints.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4430978
PhD Candidate Qiancheng Wang and Dr. Li Wan have recently published a paper. Understanding the operations of cities and informing policymaking through simulating urban change processes has been a long-lasting endeavour of generations of urban modellers. Digital twins, as an emerging technology originated in engineering and manufacturing, features a simulation process that amalgamates information from various, real-time sources to construct a virtual representation of physical products or systems. One particular urban modelling challenge is to capture the transformative yet nuanced changes of activity patterns at the individual level and understand the associated wider impacts at the city level such that pre-emptive measures could be considered... [Read the full paper]
Dr. Li Wan and PhD Candidate Hao Zhang have recently published a paper. This paper investigates intra-week variability of transport emissions using 2019 English National Travel Survey data. The unique lens of emissions variability sheds new light on the conceptualization, measurement and challenges of sustainable travel. Specifically, our analysis shows significant heterogeneity along three dimensions, (1) intra-week travel emissions; (2) the level and the variability of weekly emissions within each generic socio-economic group; and (3) latent emissions profiles across the population, which are identified using a latent profile model. [Read the full paper]
Dr. Li Wan has recently published a paper: City digital twins (CDTs), as digital replica of urban systems and development processes, have been heralded as the next-generation technology for urban planning and management. Arguably, the concept of CDTs is not new. Prior to CDTs, applied urban modelling has been playing a pivot role in supporting city and infrastructure planning since the 1960s. Examining CDTs in relation to conventional urban models can thus offer valuable insights into their nature, potential, and challenges. Such a comparative, reflective exercise, however, remains rare. This commentary aims to share insights and reflections from a dedicated applied urban modelling (AUM) community. [Read the full paper]
PhD candidate Emily Tianyuan Wang, Dr. Li Wan, and Prof. Helen X.H. Bao have recently published a new paper, titled "Land-use Efficiency and Local Government Revenue: Evidence of 272 Chinese cities using a novel structural equation modelling approach".
The unprecedented urbanisation observed in leading developing countries has placed immense pressure on effective and efficient land management. However, quantifying the interdependence between land-use efficiency, local government revenue, employment and infrastructure development whilst controlling for significant cross-city differences remains a gap in the literature... [Read the full paper]
PhD candidate Hao Zhang has recently publisehd university sustainability article.
The research hinged on a comprehensive survey rolled out to the University's staff between February 23 and April 5, 2023. Out of 330 participants, 170 active drivers provided invaluable input, leading to a rich dataset of 5,780 observations. The survey evaluated the impact of 12 distinct policy interventions across categories: Park & Ride, Carpooling, and City-based measures. To unravel the complexities of sustainable transit, the study employed a blend of scenario analysis, logit models, and latent class analysis. The University's Transport and Travel Team played an instrumental role, ensuring the survey's relevance and its alignment with present-day mobility challenges. [Read the full article]
Research associate Dr. Jerry Chen and Dr. Li Wan have recently published a new paper on PLOS ONE.
Mental health in the UK had deteriorated compared with pre-pandemic trends. Existing studies on heterogenous wellbeing changes associated COVID-19 tend to segment population based on isolated socio-economic and demographic indicators, notably gender, income and ethnicity, while a more holistic and contextual understanding of such heterogeneity among the workforce seems lacking. This study addresses this gap by 1) combining UK time use surveys collected before and during COVID-19, 2) identifying latent lifestyles within three working mode groups, and 3) quantifying nuanced experiential wellbeing (ExWB) changes across workers of distinct lifestyles. [Read the full paper]
Congratulations to Emily Tianyuan Wang, a PhD candidate in our group, who has recently won this year's Cambridge-McKinsey Risk Prize for her essay 'What makes a city to fail?'. As the winner, Emily has been awarded a prize of £3,000 at the 15th Risk Summit on 26th June 2024, attended by finance, industry, and academic delegates. Emily would like to extend her sincere thanks to Danny Ralph (Academic Director, Cambridge Center for Risk Studies), Fransje van der Marel (Senior Partner, McKinsey & Company), Andrew Freeman (Risk Fellow, Cambridge Center for Risk Studies). [Read more about the 15th Risk Summit]
As planning academics living and working in Cambridge, we have become acutely aware of the mismatch between professional and public discourses on what it means for the city to grow. Particularly, the term ‘growth’ carries varying meanings for different individuals. This public event aims to open up dialogues about 1) what it means for Cambridge to grow, and 2) how such a variety of perceptions could enable new visions of city development, drive behavioural changes and address major challenges through novel policymaking processes.
As of June 4th, 2024, we have received 192 survey responses reflecting public opinions. We sincerely appreciate the valuable contributions from all participants. [Read more on CRASSH website]
Dr. Jerry Chen and Dr. Li Wan are one of the winning teams for the AI-deas Challenge, one of five to be selected from over 70 submissions. They will investigate how local authorities in England are using AI to make decisions about issues such as placemaking, land use and mobility, and sustainable water supply systems to create public value.
This interdisciplinary project is in collaboration with the Department of Engineering and the Department of Computer Science and Technology at Cambridge, led by Dr. Kwadwo Oti-Sarpong at the Centre for Smart Infrastructure and Construction, who was previously a Research Associate in Land Economy. [Read more on Land Economy's website]
Dr. Li Wan and Ilaï Bendavid have recently published a new paper, titled "Inferring trip purposes and mode substitution effect of rental e-scooters in London".
The lack of information on trip purpose and alternative mode in micromobility service usage data remains a major analytical challenge. Conventional survey method is subject to significant sampling and stated preference biases. To overcome this challenge, this paper presents a new inference method through a case study of rental e-scooters in London. [Read the full paper]
Dr. Li Wan and Jerry Chen have recently contributed a book chapter, titled "Flexible working and the future of urban mobility: a novel conceptual framework".
This paper presents a spatio-temporal framework for conceptualising and measuring working flexibility. We argue that the transition from conventional working model towards flexible working is not a simple change of workplace or working schedule, but involves transitions between latent, distinct lifestyles which can be empirically identified. The lifestyle choices are characterised by complex trade-offs between locational and time choices at both inter- and intra-day scales. The framework enables targeted and post-pandemic relevant categorisation of working patterns beyond the trichotomy of home-based, office-based and hybrid working... [Read more]
Dr. Li Wan has recently got this new book published: Originated from manufacturing and aerospace engineering, the concept of ‘digital twin’ has been celebrated as the next-generation smart city technology, with a number of high-profile applications emerging across the globe. By employing a socio-technical framework, this book critically examines the limitations and potential risks of deploying ‘digital twins’ as a generic technology to cities, and calls for a socio-technical perspective for conceptualising, developing, evaluating and governing city digital twins. The book provides both conceptual clarity and practical guidance for supporting the development of city digital twins. [Read more]
PhD candidate Jerry Chen recently participated in the 40th International Conference on Machine Learning (ICML) from 23-29 July at Hawaii Convention Center. He shared his recent work titled "Counterfactuals for subjective wellbeing panel data: Integrated application of statistical ensemble and causal forest methods".
Five members of our group, Qiancheng Wang (PhD Student), Emily Tianyuan Wang (PhD Student), Enjia Zhang (Visitng Student), Dr. Donggyun Ku (Visting Academic Researcher), and Shan Yu (MPhil Student), recently joined the 18th Computational Urban Planning and Urban Management (CUPUM) Conference at McGill Uni from 20-22 June 2023. They delivered five presentations in total for each of their recent research work.
PhD student Emily Tianyuan Wang recently participated in the 7th Smart Data Smart City (SDSC) Conference, hosted by University of New South Wales (UNSW) in Australia. She presented her recent research work titled "A novel use of latent class modelling to understand the heterogeneity of urban land use efficiency".
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: Night-time light (NTL) data provide a novel and accessible source for monitoring the spatio-temporal dynamics of urban expansion. Existing methods tend to use national/regional and temporally static thresholds for separating urban built-up areas (UBA) and non-UBA... [Read more]