I am currently working with TSU colleagues (Dr Hannah Budnitz and Prof Tim Schwanen) to address how accessibility has played a role in the spatial variation of vaccination rates.

This study employs actual place-based measures to assess the accessibility to (mass) vaccination centres in England by car and by public transport for people according to the neighbourhoods where they live, and whether this influences vaccination rates among adults between the ages of 25 and 50 years.

The paper will be submitted to the journal of Social Science & Medicine.

More information will come soon.

This study uses anonymised and aggregated GDPR-compliant Call Detail Records from mobile phone data (by CKDelta company) to explore the trajectories of mobility change during the lockdown by monitoring day-by-day temporal variation in mobility.

Time-series clustering and a multinomial LASSO logistic regression model have been employed to examine the relationship between the trend of mobility changes and socioeconomic and demographic variables, by clusters.

One paper will be submitted to the journal of Sustainable Cities and Society.

More information will be coming soon.

By elevating the risk of respiratory-related disease air pollution is a major cause of health problems. Conventional pollution exposure research focuses on where people live, without accounting for exposure during everyday mobility and time away from home. The proposed study extends recent attempts to consider daily mobility and activities outside the residence by developing and implementing a rigorous method for individual-level, dynamic and precise measurement of air quality, daily mobility and activity participation using smart sensing devices, activity-travel diaries, and dedicated algorithms for data processing. This method will act as a proof-of-concept for an externally funded large-scale study for which a proposal will be prepared.

In this project, I will use GPS tracker, portable air quality monitoring equipment and activity diaries to obtain high-precision geo-coded and time-stamped data on the air quality people enjoyed during their daily travel and out-of-home activities. 50 participants who live in Oxford city will generate highly detailed data about variations in air pollution exposure between individuals and daily activities.

I will also develop dedicated algorithms to integrate the different data and minimise measurement errors. The approach can subsequently be used to assess population-level inequalities in air quality based on people’s based on class, race, the kinds of everyday activity people undertake, and where in geographical space they spend their time. The project is expected to start in September 2020 and last for 12 months.

Further information about this project can be found here.

Two papers have been published:

• Paper 1: An online interactive dashboard to explore personal exposure to air pollution.

• Paper 2: Geoprivacy-Preserving Publication of Mobility Data (in Korean).

This study aims to demonstrate the spatio-temporal variability of exposure to air pollution people enjoyed during their daily travel and out-of-home activities. It demonstrates the different approaches of exposure assessment by using GPS-based travel survey data and (estimated) hourly NO₂ concentration map generated from spatio-temporal regression Kriging (van Zoest et al, 2020).

In this study, I am collaborating with external research partners (Dr Tao Feng @ Eindhoven University of Technology and Dr Vera van Zoest @ Uppsala University).

More information coming soon.

COVID-19 pandemic substantially changes in human mobility patterns. In particular, changes in active travel such as walking and cycling, to mitigate the risk of infection.

In this study, I am collaborating with an external research partner (Juhyeon Kwak at Research Group in Transportation Planning at the Department of Transportation Engineering at the University of Seoul).

More information coming soon.

This working report demonstrates the effectiveness of "levelling up regional economic resilience" projects as a part of the balanced regional development plan of the Yoon government. I have explored inequalities in transportation accessibility to motorway service areas, whereas taking out the role of transportation and regional economic hubs in South Korea. In short, I suggested implementing a Mobility-as-a-Service (MaaS) platform, which is capable of providing improved travel experiences to the people who are willing to access areas of industrial parks or travel attractions over regions in South Korea.

All source R code and data necessary for the replication of figures are available at https://github.com/wondolee/KRILA.brief.2022.

The 'Oxford COVID-19 Impact Monitor' project develops an online interactive digital dashboard showing changes in people's everyday mobility during the COVID-19 outbreak since 3 March 2020. It hopes to shed light on the relationships between mobility, infection and demand for hospital beds and ventilators. Using big data analytics the project is a collaborative effort of University of Oxford researchers across multiple departments. The online dashboard is publicly accessible and updated on the basis of daily, anonymised and aggregated mobile phone location data.

In this project, I am responsible for the collection and development of the geographical datasets; these include data about essential premises that have remained open during the UK's national lock-down, such as supermarkets, parks, and hospitals. He has also been pushing the research team to focus the estimation of the mobility indicators on the spatial scales and zones that are used by stakeholders, such as the NHS hospital catchment areas which are used by clinical commissioning groups in NHS England.

Learn more about population movements over the course of pandemic across the UK with Oxford COVID-19 Impact Monitor.

Recently, I have been served to collect and process the geographical datasets for Oxford COVID-19 Impact Monitor project. I think this is where my interest began to demonstrate the association between local socioeconomic status and mobility reductions in times of pandemic, and to how extent.

This study uses mobile phone data (i.e. CDRs from CKDelta company) to examine how socioeconomic status was associated with the extent of mobility reduction during the Spring 2020 lockdown in England while considering both potentially confounding effects and spatial dependency and heterogeneity.

One paper has been published in the journal of Health & Place:

• Paper 1: The association between socioeconomic status and mobility reductions in the early stage of England’s COVID-19 epidemic

You can also access the latest preprint version through medRxiv.

The daily rhythms of the city, the ebb and flow of populations as they undertake routine activities, impact on the cause and spatio-temporal manifestation of urban problems.

I was leading this project when I was affiliated with BDC@MMU as Research Associate, to engage in evaluating the impact of population flows on the spatial and temporal patterning of crime, i.e., crime hot spots. This requires calculate spatially and temporally sensitive population denominators as well as explore the relation between population trip motivation and the characteristics of the urban environment. The major finding of this project indicate the importance of calculating the exposed population, the population present in a spatial unit at a given time that holds the capacity to play an active role as an offender, victim or guardian, when identifying crime hot spots.

Two papers have been published:

• Paper 1: The 'Exposed' Population, Violent Crime in Public Space and the Night-time Economy in Manchester, United Kingdom in the journal of European Journal on Criminal Policy and Research.

• Paper 2: The Influence of Intra-Daily Activities and Settings upon Weekday Violent Crime in Public Spaces in Manchester, UK in the journal of European Journal on Criminal Policy and Research.

For more information on this research project, please contact Prof Jon Bannister.

This project was commissioned by Greater Manchester Police (GMP) to support the development of a ‘Data Science’ analytics capability to inform better strategic and operational decision-making across the force. This project commenced in November 2016.

I was involved in this project for the development of bespoke analytical approaches for policing demand, which aims to understand the evidence-based policing demand focused on people, places, and their partnerships by applying advanced quantitative methodologies, mainly using Geo-statistics and machine-learning techniques (for Domestic Abuse study).

The aims of the project are:

• To ensure that the ‘Data Science – Operational Analytics’ project serves to complement and enhance existing GMP demand analysis outputs.

• To deliver research out with the capability and capacity of GMP in-house analytical services.

• To ensure that the research is advanced via a co-production approach to inform better research design and the development of strategic and operational products.

Recently, one paper has been published as the part of Special Issue "Big Data in the City" in the Journal of Urban Studies in 2021 as open access publishing:

• Paper 1: Understanding policing demand and deployment through the lens of the city and with the application of big data.

For more information on this research project, please contact Prof Jon Bannister.