What makes a place busy? Characterising the spatiotemporal elements of the ambient population using a range of data sources
Lead Research Organisation:
University College London
Department Name: Geography
Abstract
The PhD project on the topic "What makes a place busy? Characterising the spatiotemporal elements of the ambient population using a range of data sources" is offered
by the UCL Department of Geography and Consumer Data Research Centre
(www.cdrc.ac.uk). The primary supervisor is Professor James Cheshire and the
secondary one is Dr Stephen Law. The research will be carried out in association with
GHD Group Movement Strategies, a leading people movement consultancy, which
supplies mobility datasets to be analysed in this project
(https://www.ghd.com/en/about-us/ghd-movement-strategies.aspx).
The proposed PhD aims to combine individual-based data from mobile devices (GPSbased) and place-based data measuring footfall (via CCTV) to enhance the
quantification of ambient populations in urban areas. This will provide a better
understanding of dense urban situations such as large stadia, transport hubs, and
urban town centres to generate evidence that informs urban policies.
Through the programme, I will acquire skills in data science and machine learning for
analysing mobility and imagery datasets as well as develop novel techniques for their
validation. This will help to characterize the spatial and temporal population profiles of
places at different scales. Providing the framework for utilising and modelling the
datasets of interest will help in planning, designing, and operating crowded places with
the objectives of making them safer, maximising capacity, enhancing the visitor
experience, and increasing profitability. For instance, at the local scale, data may be
used to monitor movement density and to detect risks and anomalies in transport hubs
and large-scale events (stadia, festivals, concerts) and/or at the national scale,
characterising the health of urban retail centres (volume, retail turn-over).
Furthermore, through the PhD thesis and academic papers, I will link the mobility data
sources to urban geography and urban planning issues, with the aim of creating output
that is innovative and influential on urban policy, smart city solutions as well as future
research. Thus, both the public and private sectors would benefit from the findings of
this project.
by the UCL Department of Geography and Consumer Data Research Centre
(www.cdrc.ac.uk). The primary supervisor is Professor James Cheshire and the
secondary one is Dr Stephen Law. The research will be carried out in association with
GHD Group Movement Strategies, a leading people movement consultancy, which
supplies mobility datasets to be analysed in this project
(https://www.ghd.com/en/about-us/ghd-movement-strategies.aspx).
The proposed PhD aims to combine individual-based data from mobile devices (GPSbased) and place-based data measuring footfall (via CCTV) to enhance the
quantification of ambient populations in urban areas. This will provide a better
understanding of dense urban situations such as large stadia, transport hubs, and
urban town centres to generate evidence that informs urban policies.
Through the programme, I will acquire skills in data science and machine learning for
analysing mobility and imagery datasets as well as develop novel techniques for their
validation. This will help to characterize the spatial and temporal population profiles of
places at different scales. Providing the framework for utilising and modelling the
datasets of interest will help in planning, designing, and operating crowded places with
the objectives of making them safer, maximising capacity, enhancing the visitor
experience, and increasing profitability. For instance, at the local scale, data may be
used to monitor movement density and to detect risks and anomalies in transport hubs
and large-scale events (stadia, festivals, concerts) and/or at the national scale,
characterising the health of urban retail centres (volume, retail turn-over).
Furthermore, through the PhD thesis and academic papers, I will link the mobility data
sources to urban geography and urban planning issues, with the aim of creating output
that is innovative and influential on urban policy, smart city solutions as well as future
research. Thus, both the public and private sectors would benefit from the findings of
this project.
Organisations
People |
ORCID iD |
James Cheshire (Primary Supervisor) | |
Michal Iliev (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000592/1 | 30/09/2017 | 29/09/2027 | |||
2872654 | Studentship | ES/P000592/1 | 30/09/2023 | 29/09/2026 | Michal Iliev |