Scalable Analytical Framework for Spatio-temporal Data Analysis

Lead Research Organisation: University of Liverpool
Department Name: Geography and Planning

Abstract

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P000401/1 30/09/2017 29/09/2024
1949039 Studentship ES/P000401/1 24/09/2017 23/09/2021 Nikolaos Patias
 
Description This work presents a scalable analytical framework for understanding spatio-temporal neighbourhood change.

In the first part, the focus is on population change, using a sequence analysis approach. We use gridded cell Census data for Great Britain from 1971 to 2011 with 10-year intervals, creating neighbourhood typologies for each Census year. These typologies are then used to analyze transitions of grid cells between different types of neighborhoods and define representative trajectories of neighborhood change. The results reveal seven prevalent trajectories of neighbourhood change across Great Britain, identifying neighbourhoods which have experienced stable, upward and downward pathways through the national socioeconomic hierarchy over the last four decades.

In the second part, the focus is on change in built environment urban structure. Urban structure has been proved to be an important factor guiding urban smart growth policies that promote sustainable urban environments and improve neighbourhood social cohesion. This piece of work draws on a series of unique historical datasets obtained from Ordnance Survey, covering the largest British urban areas over the last 15 years (2001-2016) to develop a set of twelve indicators and a composite Sustainable Urban Development Index to establish the spatial and temporal structure of changes in urban structure. The results show that there is a uniform increase in urban structure sustainability of areas in and around city centres and identify that the primary built environment feature driving these improvements was an increase in walkable spaces.
Exploitation Route The outcome of this project is relevant to public policy, particularly to policies focusing on long term socioeconomic inequalities. The UK stands out as one of the most unequal countries in the industrialised world. Yet, little is known about the local structure of these inequalities. Hence, the results of this work offer the opportunity to understand long term socioeconomic inequalities at small geographic level (i.e. grids). Finally, the grids can be aggregated at different geographic levels so to understand iintra-regional and inter-urban inequalities at the neighbourhood level in Britain.
Sectors Communities and Social Services/Policy

Environment

Healthcare

Retail

Transport
URL https://link.springer.com/chapter/10.1007/978-3-030-14745-7_13
 
Description Part of my findings have been used in the first report of the UK2070 commission. The UK2070 Commission is an independent inquiry into the deep- rooted spatial inequalities in the United Kingdom.
First Year Of Impact 2019
Sector Communities and Social Services/Policy,Healthcare
Impact Types Societal

Economic

Policy & public services
 
Title extRatum: Summary Statistics for Geospatial Features 
Description Provides summary statistics of local geospatial features within a given geographic area. It does so by calculating the area covered by a target geospatial feature (i.e. buildings, parks, lakes, etc.). The geospatial features can be of any type of geospatial data, including point, polygon or line data. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact It can be used for geospatial data cleaning or/and to create simple indicators for built environment characteristics. This tool can be used to track performance of different areas across local areas, regions or countries.