EPSRC Centre for Doctoral Training in Geospatial Systems

Lead Research Organisation: Newcastle University
Department Name: Sch of Engineering

Abstract

On a daily basis huge amounts of geospatial data and information that record location is created across a wide range of environmental, engineered and social systems. Globally approximately 2 quintillion bytes of data is generated daily which is location based. The economic benefits of geospatial data and information have been widely recognised, with the global geospatial industry predicted to be worth $500bn by 2020. In the UK the potential benefits of 'opening' up geospatial data is estimated by the government to be worth an additional £11bn annually to the economy and led to the announcement of a £80m Geospatial Commission.

However, if the full economic benefits of the geospatial data revolution are to be realised, a new generation of geospatial engineers, scientists and practitioners are required who have the knowledge, technical skills and innovation to transform our understanding of the ever increasingly complex world we inhabit, to deliver highly paid jobs and economic prosperity, coupled with benefits to society.

To seize this opportunity, the Centre for Doctoral Training in Geospatial Systems will deliver technically skilled doctoral graduates equipped with an industry focus, to work across a diverse range of applications including infrastructure systems, smart cities, urban-infrastructure resilience, energy systems, spatial mobility, structural monitoring, spatial planning, public health and social inclusion. Doctoral graduates will be trained in five core integrated geospatial themes:

Spatial data capture and interpretation: modern spatial data capture and monitoring approaches, including Earth observation satellite image data, UAVs and drone data, and spatial sensor networks; spatial data informs us on the current status and changes taking place in different environments (e.g., river catchments and cities).

Statistical and mathematical methods: innovative mathematical approaches and statistical techniques, such as predictive analytics, required to analyse and interpret huge volumes of geospatial data; these allow us to recognise and quantify within large volumes of data important locations and relationships.

Big Data spatial analytics: cutting edge computational skills required for geospatial data analysis and modelling, including databases, cloud computing, pattern recognition and machine learning; modern computing approaches are the only way that vast volumes of location data can be analysed.

Spatial modelling and simulation: to design and implement geospatial simulation models for predictive purposes; predictive spatial models allow us to understand where and when investment, interventions and actions are required in the future.

Visualisation and decision support: will train students in modern methods of spatial data visualisation such as virtual and augmented reality, and develop the skills on how to deliver and present the outputs of geospatial data analysis and modelling; skills required to ensure that objective decisions and choices are made using geospatial data and information.

The advanced training received by students will be employed within interdisciplinary PhD research projects co-designed with 40 partners ranging from government agencies, international engineering consultants, infrastructure operators and utility companies, and geospatial technology companies; organisations that are ideally positioned to leverage of the Big Data, Cloud Computing, Artificial Intelligence and Internet of Things (IoT) technologies that are predicted to be the key to "accelerating geospatial industry growth" into the future.

Throughout their training and research, students will benefit from cohort-based activities focused on group-working and industry interaction around innovation and entrepreneurship to ensure that our outstanding researchers are able to deliver innovation for economic prosperity across the spectrum of the geospatial industry and applied user sectors.

Planned Impact

We have identified the potential impact of the CDT in consultation with 44 partner organisations, ensuring we are meeting the needs of potential beneficiaries. The impacts that we will develop robust pathways to achieve include:

Economic:
Our graduates will be a key pool of knowledge and skills to deliver the annual £11bn of economic benefit to the UK from 'opening-up' geospatial data. Their advanced skills in a rapidly changing technological field will help the UK geospatial industry realise the predicted global annual growth of 13.8% and transform the use of geospatial data and technology in smart cities, urban-infrastructure resilience, energy systems and structural monitoring.
Through continuous two-way engagement with our partners we will shape and deliver industry relevant PhD projects that apply students' unique training. Ongoing knowledge exchange with industry will be facilitated through regular interaction with the centre, the Industrial Advisory Board and partner participation at the Innovation Festival, CDT Assembly and Challenge Week events. We will work with the recently announced £80m Geospatial Commission to ensure the translation of new methods, techniques and technology to the broadest possible user base; using our partnerships with professional bodies to recognise the opportunities and challenges to realising the economic benefits of geospatial data.
SME and start-ups are will be major drivers of global geospatial industry growth. Innovation and entrepreneurial training will position our graduates to act as a catalyst of the growth needed in the UK to remain internationally competitive. Working with Satellite and Digital Catapults, and the £30million National Innovation Centre for Data, we will foster a 'full-circle' engagement with SME's and start-ups; to ensure our graduates understand the drivers for innovation, facilitate co-production and ensure the timely adoption of academic driven advances for economic growth.

Societal:
We have recognised the significant role geospatial data will play in providing the evidence for improved planning and response to significant global societal problems. The interdisciplinary PhD research conducted within the CDT will provide new insight and understanding in climate impacts and adaption, sustainable cities, and healthy living and aging. Our graduates will engage with key international and national organisations (e.g., Cities Resilience Programme of the World Bank, UK National Infrastructure Commission) to ensure the widest adoption of their research.

Academic:
Our graduates will form the next generation of geospatial scientists and engineers vital for interdisciplinary research at the engineering-societal-environment nexus. Their combined skills in geospatial technology and methods, along with advanced mathematical, statistical and computing skills, will provide the UK with a unique resource pool of academic leaders. The research produced by the centre, sustained and embedded by the skilled workforce it creates, will help address the Grand Challenges of the UK Industrial Strategy; AI and the Data Driven Economy, Future Mobility and an Aging Society.

To maximize academic outreach we will provide a Geospatial Systems Resource Portal that will allow researchers to access the new techniques and methods developed. Software and related methods will be open source, and tutorials and training guides will be developed as a matter of routine. We will organise CPD courses based on our unique integrated training in Geospatial Systems, open to cohorts from other CDTs within the digital economy space. We will foster cross-UKRI translation and learning by working with related CDTs; the ESRC CDT in Data Analytics and Society and NERC CDT in Data, Risks and Environmental Analytical Methods. Via our 9 international research partners our unique training approach and strong emphasis on interdisciplinary research will become internationally impactful.

Organisations

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023577/1 01/04/2019 30/09/2027
2281589 Studentship EP/S023577/1 01/10/2019 30/09/2023 Kristina Wolf
2281581 Studentship EP/S023577/1 01/10/2019 30/09/2023 Mingyu Zhu
2299573 Studentship EP/S023577/1 01/10/2019 23/12/2023 Sally Crudge
2299639 Studentship EP/S023577/1 01/10/2019 30/09/2023 Anna Klimkowska
2281604 Studentship EP/S023577/1 01/10/2019 30/09/2023 David Alvarez Castro
2299620 Studentship EP/S023577/1 01/10/2019 30/09/2024 Tahsinur Khan
2281614 Studentship EP/S023577/1 01/10/2019 30/09/2023 Rachael Sanderson
2281634 Studentship EP/S023577/1 01/10/2019 30/09/2023 Aleksandra Zaforemska
2425151 Studentship EP/S023577/1 01/09/2020 30/09/2024 Athanasia Apostolopoulou
2422800 Studentship EP/S023577/1 01/10/2020 30/09/2024 Samuel Valman
2435696 Studentship EP/S023577/1 01/10/2020 22/01/2025 Richard Burke
2435725 Studentship EP/S023577/1 01/10/2020 30/09/2024 Adam Booth
2435741 Studentship EP/S023577/1 01/10/2020 25/05/2025 Luis Patino Velasquez
2422799 Studentship EP/S023577/1 01/10/2020 30/09/2024 Neil Sutherland
2435776 Studentship EP/S023577/1 01/10/2020 30/12/2024 Rebecca Guiney
2435707 Studentship EP/S023577/1 01/10/2020 30/09/2024 Clara Peiret-Garcia
2571906 Studentship EP/S023577/1 01/10/2020 30/09/2024 Samuel Christelow
2588531 Studentship EP/S023577/1 01/10/2021 30/09/2025 Rachel Walker
2598942 Studentship EP/S023577/1 01/10/2021 30/09/2025 Ambreen Masud
2605547 Studentship EP/S023577/1 01/10/2021 30/09/2025 Keneuoe Maliehe
2599003 Studentship EP/S023577/1 01/10/2021 30/09/2025 Christopher Larkin
2604985 Studentship EP/S023577/1 01/10/2021 30/09/2025 David Gregg
2590269 Studentship EP/S023577/1 01/10/2021 30/09/2025 Philip Home
2599007 Studentship EP/S023577/1 01/10/2021 30/09/2025 Corneliu Cotet
2588972 Studentship EP/S023577/1 01/10/2021 30/09/2025 Sophie Mann
2749917 Studentship EP/S023577/1 30/09/2022 30/09/2026 Luis Cormier
2749639 Studentship EP/S023577/1 30/09/2022 30/09/2026 Luke Taylor
2749968 Studentship EP/S023577/1 01/10/2022 30/09/2026 David Fountain
2749565 Studentship EP/S023577/1 01/10/2022 30/09/2026 Eleanor Myall
2750190 Studentship EP/S023577/1 01/10/2022 30/09/2026 Adewale Falaye
2749589 Studentship EP/S023577/1 01/10/2022 30/09/2026 Francisco Salgado Castillo
2749683 Studentship EP/S023577/1 01/10/2022 30/09/2026 Carrow Morris-Wiltshire
2749551 Studentship EP/S023577/1 01/10/2022 30/09/2026 Olivia Fairless
2749540 Studentship EP/S023577/1 01/10/2022 30/09/2026 Ruth Dunn
2750242 Studentship EP/S023577/1 01/10/2022 30/09/2026 Yashvini Shukla
2749598 Studentship EP/S023577/1 01/10/2022 30/09/2023 Stuart Gordon
2763649 Studentship EP/S023577/1 01/10/2022 30/09/2026 Oshadee Jayamanne
2884587 Studentship EP/S023577/1 30/09/2023 30/09/2027 Lilian Akanazu
2884205 Studentship EP/S023577/1 30/09/2023 01/10/2027 Holly Dancer
2884322 Studentship EP/S023577/1 30/09/2023 30/09/2027 Matthew Causon
2884315 Studentship EP/S023577/1 30/09/2023 30/09/2027 Ayisha Dubi
2877249 Studentship EP/S023577/1 01/10/2023 30/09/2027 Matthew Chapman
2875994 Studentship EP/S023577/1 01/10/2023 30/09/2027 Christopher Drowley
2876286 Studentship EP/S023577/1 01/10/2023 30/09/2027 Thomas Goldring
2876261 Studentship EP/S023577/1 01/10/2023 30/09/2027 Michael Jones
2876001 Studentship EP/S023577/1 01/10/2023 30/09/2027 Kaitlyn Ries
2884565 Studentship EP/S023577/1 01/10/2023 30/09/2027 Helen Haile
2875952 Studentship EP/S023577/1 01/10/2023 30/09/2027 Nadia Skifa
2875980 Studentship EP/S023577/1 01/10/2023 30/09/2027 Hope Irvine
2875949 Studentship EP/S023577/1 01/10/2023 30/09/2027 Roy Johnson