Francisco Rowe

Francisco Rowe

Senior Lecturer in Quantitative Human Geography

University of Liverpool

Biography

Francisco Rowe is the lead of the Geographic Data Science Lab and Senior Lecturer in Quantitative Human Geography at the Department of Geography and Planning within the University of Liverpool. His areas of expertise are: internal & international migration; human mobility; and geographic data science. Francisco is featured in the Experts Database of the United Nations Network on Migration and two of his projects on Big Data, machine learning and migration are listed in the Data Innovation Directory of the International Organization for Migration. He has been invited to present his research at the United Nations Population & Development Division in New York and works closely with the Global Migration Data Analysis Centre within International Organization for Migration, the United Nations Economic Commission for Latin America and the Caribbean, the UK2070 Commission, UK’s government organisations, including the Ordnance Survey and the ONS Data Campus, and commercial companies, Geolytix. His work contributed to the United Nations Expert group meeting on `sustainable cities, human mobility and international migration', and the ONS Government Statistical Service Advisory Committee. Francisco is the current managing editor of REGION (2022-present), the journal of the European Regional Science Association (2018-present) and social media editor at the Journal of the Royal Statistical Society Series A (2021-present). The international reach of his research has been recognised by an award for the best paper published in the journal of Geographical Systems (2021) and in Spatial Economic Analysis (2018) and having top articles in the top 10 most read articles in Spatial Economic Analysis (2017-present), Transportation Research Part C (2018-2019) & Population Studies (2018-present).

Download my CV.

Interests
  • Human Mobility and Migration
  • Economic Geography and Spatial Inequality
  • Geographic Data Science
Education
  • PhD in Economic Geography, 2013

    University of Queensland

  • MSc in Regional Science, 2008

    Universidad Catolica del Norte

  • BA in Business Management, with specialisation in Economics, 2007

    Universidad Catolica del Norte

Recent Posts

Projects

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Using large scale social media data to measure perceptions towards immigration

Using large scale social media data to measure perceptions towards immigration

This project aims to develop analytical methods to monitor public opinions towards immigration using Twitter data and machine learning.

Using Machine Learning to Estimate Global Bilateral Migration Flows

Using Machine Learning to Estimate Global Bilateral Migration Flows

This project aims to generate annual country-to-country migration estimates across the world.

COVID19 Generating actionable evidence for containing misinformation to prevent discrimination

COVID19 Generating actionable evidence for containing misinformation to prevent discrimination

The project aims to generate fundamental and timely evidence for how misinformation and fake news spreads across media platforms.

Sensing global patterns and trajectories of socio-economic inequality

Sensing global patterns and trajectories of socio-economic inequality

This project aims to measure and analyse the evolution of spatial inequality across the world using remote sensing.

Understanding and Predicting the Long-term Labour Market and Migration Trajectories of Immigrants and Their Children in the United Kingdom

Understanding and Predicting the Long-term Labour Market and Migration Trajectories of Immigrants and Their Children in the United Kingdom

This project aims to investigate how the educational and employment trajectories of immigrants and their children in the UK evolve and interact; and, how factors related to their residential environment, early life context and critical life transitions shape these trajectories between 1991-2017.

Using satellite imagery to measure the evolution of cities

Using satellite imagery to measure the evolution of cities

The project aims to develop and employ analytical approaches to measure the evolution of cities using machine learning and satellite imagery.

Understanding the declining trend in internal migration in Europe

Understanding the declining trend in internal migration in Europe

The project aims to establish the start and pace of the migration decline in 18 European countries.

Recent & Upcoming Talks

Understanding Human Mobility in Britain During the COVID-19 Pandemic Using Facebook Data
Existing empirical work has focused on assessing the effectiveness of non-pharmaceutical interventions on human mobility to contain the spread of COVID-19. Less is known about the ways in which the COVID-19 pandemic has reshaped the spatial patterns of population movement within countries. Anecdotal evidence of an urban exodus from large cities to rural areas emerged during early phases of the pandemic across western societies. Yet, these claims have not been empirically assessed. Traditional data sources, such as censuses offer coarse temporal frequency to analyse population movement over short-time intervals. Drawing on a data set of 21 million observations from Facebook users, we aim to analyse the extent and evolution of changes in the spatial patterns of population movement across the rural-urban continuum in Britain over an 18-month period from March, 2020 to August, 2021. Our findings show an overall and sustained decline in population movement during periods of high stringency measures, with the most densely populated areas reporting the largest reductions. During these periods, we also find evidence of higher-than-average mobility from highly dense population areas to low densely populated areas, lending some support to claims of large-scale population movements from large cities. Yet, we show that these trends were temporary. Overall mobility levels trended back to pre-coronavirus levels after the easing of non-pharmaceutical interventions. Following these interventions, we also found a reduction in movement to low density areas and a rise in mobility to high density agglomerations. Overall, these findings reveal that while COVID-19 generated shock waves leading to temporary changes in the patterns of population movement in Britain, the resulting vibrations have not significantly reshaped the prevalent structures in the national pattern of population movement.
Understanding Human Mobility in Britain During the COVID-19 Pandemic Using Facebook Data