ACADEMIC RESOURCES.
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OVERVIEW
This tab outlines research at The Bartlett that has used big data as part of its methodology. Please keep in mind that most urban design research currently uses big data as a complimentary method in a mixed methods approach. Find the latest research at The Bartlett here.
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You can also find relevant data sources and formats you can consider for your urban design analysis or design on the 'general datasets' tab.
research @ the bartlett
GENERAL datasets
NEWS, IDEAS and INSPIRATION
research @ the bartlett
Research has been organised by data used:
economic data
Defining urban clusters to detect agglomeration economies
This paper focuses on the spatial and economic complexity of the mechanisms defining agglomeration within and between cities.
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Data Used: French census and national statistics data, CORINE Land Cover data
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Researcher: Dr Elsa Arcaute
The nested structure of urban business clusters
Using longitudinal business microdata from the Office for National Statistics, we look at the evolution of clusters which spans from very local groups of businesses to the metropolitan level, in 2007 and in 2014, so that the changes stemming from the financial crisis can be observed.
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Data Used: The Business Structure Database – Provided by ONS. The dataset supporting the conclusions of this article (similarity matrix between LSOA, Source: ONS) is available in a FigShare repository, 10.6084/m9.figshare.8035961
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Researcher: Dr Elsa Arcaute
Visualising urban gentrification and displacement in Greater London
Using six sets of thematic data from 2001 and 2011 at the neighbourhood level, this study proposes five types of gentrification and displacement by using Chapple and Zuk’s theoretical framework. London was selected as a case study.
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Data Obtained from the Office for National Statistics (ONS), the Greater London Authority (GLA) and the Land Registry. Details on data used to be found on Zhang's GitHub profile.
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Researcher: Yuerong Zhang
environmental data
Circular cities and why we need them
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In this paper Williams investigates why the current state-of-the-art conceptualisation for circular economy (RESOLVE) is inadequate when applied to a city.
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Data used: European Union Waste Shipment Statistics, 2014 International Energy Agency (IEA), 2008
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Researcher: Dr Joanna Williams, Director of the Circular Cities Hub
Circular Cities: Challenges to Implementing Looping Actions
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In this paper we explore the challenges facing the implementation of looping actions in cities. Using a mixed methods approach, we identify 58 challenges to looping actions across eight themes.
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Researcher: Dr Joanna Williams, Director of the Circular Cities Hub
The deployment of decentralised energy systems as part of the housing growth programme in the UK
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In this paper we explore the challenges facing the implementation of looping actions in cities. Using a mixed methods approach, we identify 58 challenges to looping actions across eight themes.
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Data used: Energy data produced by agencies Renewables East, 2008 South East Renewable Energy Statistics, 2009 , Ecotricity (2007)
Researcher: Dr Joanna Williams, Director of the Circular Cities Hub
housing and property data
Colouring London is a free knowledge exchange platform, designed by UCL to collate, collect, generate, visualise and make accessible, statistical data for every building in London.
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Spatial data: Ordnance Survey MasterMap (OSMM) polygons/ building footprints
Researchers: Team of collaborators
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Housing submarkets can be defined as a set of dwellings that are reasonably close substitutes with one another, but poor substitutes between other submarkets. This research argues similarities within submarkets are not only captured by its building and location characteristics but also in how each dwelling is inter-connected within its local area and embedded to the rest of the system.
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Data used: Street Network – OS Merdian 2, House price data – Land Registry
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Researcher: Prof Alan Penn
Mind the Poorest: Social Housing Provision in Post-crisis Romania
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This paper reflects on recent social housing developments in Romania.
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Data used: EUROSTAT 2014. House Price Index database. Romania’s housing stock by tenure as % of total housing stock
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Researcher: Dr Catalina Turcu
Creating a new dataset to analyse house prices in England
House price data deficiencies hinder UK housing market research. House price research in the UK is limited by lack of an open and comprehensive house price database that contains transaction price alongside individual property characteristics. This research outlines one approach which addresses this deficiency in England.
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Data used: Land Registry PPD, Ordnance Survey (OS) MasterMap, OS AddressBase Plus, total floor area information from Domestic Energy Performance Certificates (EPCs)
Researchers: Team of collaborators
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The accessibility effect on house price ranges from strongly significant in London to insignificant in Birmingham. In general, the economic effect is weaker in smaller, more car dependent cities, with a greater proportion of the population employed in the manufacturing sector, and is stronger in cities that are denser, more walkable with greater productivity and a greater proportion of residents in the education sector. This exploration therefore suggests that the economic value placed upon urban accessibility may be related to a combination of mobility factors, its urban form and its economic profile.
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Data used: House price data – Land Registry and Nationwide Building Society, Street Network – OS Merdian 2, Cities Dataset - Office of National Statistics (ONS) and the Centre for Cities dataset (Centre for Cities, 2016)
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Researcher: Prof Alan Penn
Take a Look Around: Using Street View and Satellite Images to Estimate House Prices
The researchers make use of traditional housing features such as age, size and accessibility as well as visual features from Google Street View images and Bing aerial images in estimating the house price model. The research explores the use of non-linear vs. linear methods to fuse these cues with conventional models of house pricing, and show how the interpretability of linear models allows them to directly extract the visual desirability of neighbourhoods as proxy variables that are both of interest in their own right, and could be used as inputs to other econometric methods.
Data used: OS Merdian 2, House price data - real estate, deep learning, convolutional neural network, hedonic price models, machine vision, London
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Researcher (UCL): Stephen Law
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Based on a design audit of 142 housing developments across England, and correlations with data on market, contextual and design governance factors, a number of conclusions were drawn. These concern the type of housing that is being delivered, what is going right and wrong, and why there is such a variation in practice across the country.
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Data used: property data for design dimension
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Researcher: Prof Matthew Carmona
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What is Governed in Cities: Residential Investment Landscapes and the Governance and Regulation of Housing Production. This project examines the relationships between contemporary investment flows into the housing markets of major European cities and the arrangements and public policy instruments that are designed to govern them.
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Data used: Real Estate, investment data, housing markets
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Researcher: Prof Mike Raco
public space and urban life data
London’s local high streets: The problems, potential and complexities of mixed street corridors
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This paper examines the ‘problem’ of mixed street corridors through the lens of London's local high streets (main streets).
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Data used: London-wide data covering issues of development potential, employment, transport accessibility, resident population, access to healthcare, and pollution
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Researcher: Prof Matthew Carmona
The paper presents a methodology for quantifying streetspace designation across entire cities. The new street level data is generated using a geocomputational approach that both allows for a quantitative citywide description of streetspace at a micro-scale and that can be replicated across multiple cities.
Data used: geocomputational, urban physical environment digital mapping data
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Researcher: Nicolas Palominos, Dr Duncan A. Smith
social media data
Researching Urban Life Through Social Media
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The life of any city today, even a modestly sized one, will more than likely leave digital traces on some kind of social media platform. In this chapter, we focus on qualitative approaches to researching urban life through social media, while also pointing to some data analytics approaches that can inform qualitative approaches.
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Data used: Social media data
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Researcher: Dr Susan Moore
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The paper examines of how urban exploration can be enriched by adding a spatial feature which is social media data that is absent in current navigation systems.
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Data used: Social media data
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Researcher: Ava Fatah
spatial data
Building stock energy modelling in the UK: the 3DStock method and the London Building Stock Model
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The paper explains how 3DStock models are built and the data sources used. Special emphasis is placed on the relationship of premises (the floorspace occupied by organisations) to buildings.
Data used: OS Mastermap, property taxation data collected by the Valuation Office Agency, light detection and ranging (LiDAR) data, property ownership published by HMLR, data on structural systems, materials of walls and roofs, roof types and estimated ages of buildings purchased from GeomniUK.
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Researcher: Dominic Humphrey
Cities and regions in Britain through hierarchical percolation
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This paper examines the evolution of the morphology of cities as a whole, by measuring the fractal dimension of the clusters at each distance threshold in the percolation.
Data used: OS Mastermap
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Researcher: Dr Elsa Arcaute
Exploring the Spatiality of localities: the Case of Cental Athens
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This is a past dissertation. The research uses big data and space syntax to examine spatial form across different spatial scales and for relating spatial form with social outcomes.
Researcher: Ioanna Kolovou
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Supervised by: Kayvan Karimi, The Bartlett, MRes Inter-disciplinary Urban Design
transport data
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This research aims to provide more complete insights and assessment of the underground networks’ resilience.
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Data used: Oyster data from TfL, Census data from ONS
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Researcher: Yuerong Zhang is a PhD researcher, affiliated with the Urban Design Research Group at The Bartlett
The research explore the relation between spatial pattern of makerts and its sucess regarding the popularity of static activities.
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The researcher uses Depthmath, NACH and NAIN
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Researcher: Jiawen Tu
Supervised by: Prof Laura Vaughan