Epsrc Centre Doctoral Tender

Funded Value6718389Funded PeriodApr 19 - Sep 27FunderEPSRCProject StatusActiveProject CategoryTraining GrantProject ReferenceEPS0235771On 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 themesSpatial 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 alyse 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 augmen