Professor Yan Liu

Professor

School of Earth and Environmental Sciences
Faculty of Science
yan.liu@uq.edu.au
+61 7 336 56483

Overview

Professor Yan Liu is a Geographical Information Scientist and a Quantitative Human Geographer with expertise in urban modelling, GIS, and spatial (big) data analytics. Her research themes are centred on (1) modelling urban systems through complex systems modelling and geo-simulation incorporating cellular automata (CA) and agent based modelling (ABM) to describe, understand, simulate and predict urban change processes and dynamics; and (2) spatially integrated urban and societal studies incorporating spatial data mining and big data analytics. The nature of her research is inherently multi-disciplinary, since the output of her research has a wide impact across physical/environmental and social sciences. She has convened the Spatio-Temporal Analytics Research Laboratory (STAR Lab) since 2016 as a platform providing opportunities for post-doctoral research fellows, ECRs, HDR students, visiting scholars and past students to collaborate together in developing new data and methods for addressing a range of urban and big data issues.

Research Interests

  • Urban Modelling and Geo-Simulation
    My work focus on developing cellular automat (CA) models to understand the spatio-temporal patterns, processes, and drivers of urban growth; and modelling human-environment interactions through scenario planning and geo-simulation. More recent work focuses on understanding how the decision behaviours of various stakeholders impact on the spatio-temporal processes of urban growth through an integrated CA and agent based modelling (ABM) approach. I am currently recruiting PhD students to work on: 1) developing an irregular parcel based CA and 3D CA model to simulate vertical urban growth in Brisbane; 2) a cross-cultural comparison/validation of a CA-ABM model to simulate urban growth dynamics.
  • Spatial Data Analytics
    I am interested in all aspects of spatial data analytics, including big data and spatio-temporal data mining tools and methods, with the aim to enhance our understanding on a range of social geographical and health related issues. Some on-going research in the field include: analysis and modelling of public transport services and human mobility and travel behaviours using smart card data; mining of large scale administrative data to understand (un)-neighbourliness and neighbourhood disorders; modelling of spatial access to green space, health and other services and facilities to identify disparity and inequalities.
  • 3D modelling and Geo-Visualisation
    My work in this field focuses on spatial visualisation, 3D GIS and applications in spatial skills development and education. I am currently working on a project to develop a 3D city model and implement a sequential technology-enabled curriculum in Urban Planning using 3D modelling techniques to enhance students' spatial skills and become work-ready planners.

Research Impacts

Professor Liu's research addresses a range of socio-spatial challenges in our urban and regional environments through the development of spatially-integrated research approaches which incorporate spatial data mining and big/small data analytics. Her research includes (but not limited to) accessibility, inequalities in housing and healthcare services, and neighbour interactions, in the context of ever-changing human–environment conditions such as urbanisation, population growth and climate change. Her research contributes to advance our understanding of the spatial evolutions of cities, to create new and much-needed science-based decision tools for optimising government policymaking, and to mitigate risk and improve policy outcomes for communities.

Current projects:

  • The Australian Transport Research Cloud (ATRC). This project aims to provide a common platform (data, storage, compute and tools) to support the needs of the Australian transport research community.
  • ARC DP (2017-2019) to develop new approaches to modelling human-environment interactions for sustainable coastal city development based on spatial complexity, cellular automata and agent based models.
  • Open Fund of Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University (2019-2020). Coastal cities: environmental evolution, climate change, and human adaptation
  • National Natural Science Foundation of China (NSFC) funded project (2019-2022). Ventilation based planning methods to respond urban haze supported by multi-source spatial-temporal big data.
  • QLD Gov’t Community Sustainability Action Grants (2018-20). Improved offsets for koala conservation.
  • Faculty of Science T&L Grant (2019-2020). Collaborative online learning for Geographic Information Science

Completed projects:

  • Academy of the Social Sciences in Australia (ASSA) (2018-19). Ageing well: Place, belonging, and well-being of older Chinese in Australia and China.
  • UQ Transport & Population Research Network (TPRN) Seed Fund (2019). Understanding socio-spatial connectedness for older people from culturally and linguistically diverse (CALD) backgrounds: Testing a mixed-methods approach.
  • Ministry of Research, Technology, and High Education, Indonesia (2016-18). The role of spatial planning towards better resilience to hydro-meteorological hazard. Case study: Coast area of Semarang City.
  • ARC DP (2015-2017). Un-neighbourliness: The nature, causes and outcomes of problems between neighbours using survey and large scale administrative data.
  • UQ FirstLink project (2016-2017) to analyse and map mild stoke outcomes and untreated deficits using GIS approach.
  • UQ Property and Facilities Division funded project (2015-2018) to analyse UQ public transport commuters' travel patterns and behabiours using go card and survey data.

Qualifications

  • Graduate Certificate in Higher Education, The University of Queensland
  • Doctor of Philosophy, The University of Queensland

Publications

View all Publications

Grants

View all Grants

Supervision

View all Supervision

Available Projects

  • This project draws on the understanding of the physical and eco-system evolution from existing research to develop an integrated modelling framework to simulate and plan for the spatial and temporal processes of urban development under the impact of climate change and human adaptation strategies. Specifically, it aims to 1) model contemporary urban development, urban morphology and settlement patterns to better understand the influence of different scenarios on the coastal city; 2) evaluate the impacts associated with urban development over different time horizons. Impacts may include transportation costs, land consumption, physical infrastructure costs, and changes in productivity as well as sustainability indicators; and 3) project future urban development as a means of testing uncertain environmental futures. If interested in working on this project please contact me at yan.liu@uq.edu.au.

  • Place-based health planning is an effective and innovative approach to health planning that is developed drawing on local demographic, socioeconomic, and environmental factors. It identifies and prioritises local health needs and develops and delivers locally-led, evidence-based solutions. Place-based approaches are collaborative endeavours which aim to create systematic changes for long-term outcomes by fostering community partnerships and bringing together efforts across the community, service providers and government levels. An important part of place-based planning is to understand the needs of communities. Such a planning process can be facilitated using Public Participation Geographic Information System (PPGIS). PPGIS is a spatial tool that can be used to engage the local communities and residents to capture their local knowledge, and advance their needs and goals for health services. Therefore, this PhD project aims at developing a PPGIS approach to engage local residents in order to understand and prioritise their health needs, enablers and barriers impacting on their acces to health services in order to develop planning interventions to meet people’s health needs and improve their health outcomes. If interested in working on this project please contact me at yan.liu@uq.edu.au.

  • The emergence of open and new data available from various sources have presented significant opportunities for research in the urban sciences. Entering into the new era of big data, ever-increasing quantities at near real time will ultimately change the ways in which human agents interact with each other and with the urban space they occupy and transform; these pose new challenges to urban modellers and researchers, and much effort should be devoted to conquer the aforementioned big data challenges. In this context, I welcome any project that aims at developing novel approaches for spatial (big) data monitoring, analytics, modelling and simulation in order to addresses a range of socio-spatial challenges in our urban and regional environments, including (but not limited to) accessibility, inequalities in housing and healthcare services, and neighbour interactions, in the context of ever-changing human–environment conditions such as urbanisation, population growth and climate change. If interested in working on this project please contact me at yan.liu@uq.edu.au.

View all Available Projects

Publications

Book

Book Chapter

Journal Article

Conference Publication

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Associate Advisor

  • Doctor Philosophy — Associate Advisor

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • This project draws on the understanding of the physical and eco-system evolution from existing research to develop an integrated modelling framework to simulate and plan for the spatial and temporal processes of urban development under the impact of climate change and human adaptation strategies. Specifically, it aims to 1) model contemporary urban development, urban morphology and settlement patterns to better understand the influence of different scenarios on the coastal city; 2) evaluate the impacts associated with urban development over different time horizons. Impacts may include transportation costs, land consumption, physical infrastructure costs, and changes in productivity as well as sustainability indicators; and 3) project future urban development as a means of testing uncertain environmental futures. If interested in working on this project please contact me at yan.liu@uq.edu.au.

  • Place-based health planning is an effective and innovative approach to health planning that is developed drawing on local demographic, socioeconomic, and environmental factors. It identifies and prioritises local health needs and develops and delivers locally-led, evidence-based solutions. Place-based approaches are collaborative endeavours which aim to create systematic changes for long-term outcomes by fostering community partnerships and bringing together efforts across the community, service providers and government levels. An important part of place-based planning is to understand the needs of communities. Such a planning process can be facilitated using Public Participation Geographic Information System (PPGIS). PPGIS is a spatial tool that can be used to engage the local communities and residents to capture their local knowledge, and advance their needs and goals for health services. Therefore, this PhD project aims at developing a PPGIS approach to engage local residents in order to understand and prioritise their health needs, enablers and barriers impacting on their acces to health services in order to develop planning interventions to meet people’s health needs and improve their health outcomes. If interested in working on this project please contact me at yan.liu@uq.edu.au.

  • The emergence of open and new data available from various sources have presented significant opportunities for research in the urban sciences. Entering into the new era of big data, ever-increasing quantities at near real time will ultimately change the ways in which human agents interact with each other and with the urban space they occupy and transform; these pose new challenges to urban modellers and researchers, and much effort should be devoted to conquer the aforementioned big data challenges. In this context, I welcome any project that aims at developing novel approaches for spatial (big) data monitoring, analytics, modelling and simulation in order to addresses a range of socio-spatial challenges in our urban and regional environments, including (but not limited to) accessibility, inequalities in housing and healthcare services, and neighbour interactions, in the context of ever-changing human–environment conditions such as urbanisation, population growth and climate change. If interested in working on this project please contact me at yan.liu@uq.edu.au.