Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics

Anejionu, O.C.D., Thakuriah, P.V., McHugh, A. , Sun, Y., McArthur, D., Mason, P. and Walpole, R. (2019) Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics. Future Generation Computer Systems, 98 . pp. 456-473. ISSN 0167-739X

Full text not available from this repository.

Item Type:Article
Item Status:Live Archive


The Spatial Urban Data System (SUDS) is a spatial big data infrastructure to support UK-wide analytics of the social and economic aspects of cities and city-regions. It utilises data generated from traditional as well as new and emerging sources of urban data. The SUDS deploys geospatial technology, synthetic small area urban metrics, and cloud computing to enable urban analytics, and geovisualization with the goal of deriving actionable knowledge for better urban management and data-driven urban decision making. At the core of the system is a programme of urban indicators generated by using novel forms of data and urban modelling and simulation programme. SUDS differs from other similar systems by its emphasis on the generation and use of regularly updated spatially-activated urban area metrics from real or near-real time data sources, to enhance understanding of intra-city interactions and dynamics. By deploying public transport, labour market accessibility and housing advertisement data in the system, we were able to identify spatial variations of key urban services at intra-city levels as well as social and economically-marginalised output areas in major cities across the UK. This paper discusses the design and implementation of SUDS, the challenges and limitations encountered, and considerations made during its development. The innovative approach adopted in the design of SUDS will enable it to support research and analysis of urban areas, policy and city administration, business decision-making, private sector innovation, and public engagement. Having been tested with housing, transport and employment metrics, efforts are ongoing to integrate information from other sources such as IoT, and User Generated Content into the system to enable urban predictive analytics.

Additional Information:cited By 20
Keywords:Urban big data infrastructure, Urban analytics, Spatial urban indicators, Small area assessment, Spatial big data
Subjects:F Physical Sciences > F891 Geographical Information Systems
Divisions:College of Science > School of Geography
ID Code:49423
Deposited On:19 May 2022 10:22

Repository Staff Only: item control page