COLOURING CITIES RESEARCH PROGRAMME 

 
 
 
 
 
 
The Colouring Cities Research Programme (CCRP) has been set up at the Alan Turing Institute, to facilitate collaboration between academic institutions interested in reproducing Colouring London's open code to advance research into sustainable and resilient building stocks. The CCRP also supports the United Nations' New Urban Agenda
 
CCRP partners test methods of open data capture, generation, collation, verification, visualisation and dissemination within participating cities and countries. Four integrated approaches to data provision are explored: existing open dataset collation, computational generation, crowdsourcing, and live-streaming. Our collective aim is to stimulate a rapid increase in the volume, variety, accuracy, precision and quality of open spatial data available on stocks, at building level. This is necessary to understand stock composition, performance and dynamic behaviour building stocks, and to support research and policy making relating to sustainability.
The CCRP has been designed to support the development of a network of collaboratively maintained Colouring Cities open databases. It also offers a  friendly, informal, creative, non-competitive and experimental space for multidisciplinary research into the stock. The programme currently involves researchers from six countries, bringing together expertise in computer science, AI, machine learning, urban science, data science, physics, architectural history, conservation and heritage, housing, planning and architecture.
 
Examples of research questions of particular interest to the group include: What kinds of buildings exist in the city - typology, age, use, size etc? How many of each are there and where are they located? How long do different types of building last and why and how can we help buildings adapt in a sustainable way? How useful can Colouring Cities platforms be in analysing and modelling stocks and/or in tracking  performance, reducing energy and waste flows, targeting retrofit, and improving housing quality. How can longitudinal data also  be collected and what can this tell us about survival, risk and vulnerability in stocks? Can platforms also double up as disaster management tool and how can we share learning of resilient reconstruction?Can common patterns be found across countries in relation to  building form and  deprivation, poor health and mortality? How similar or different are stocks across countries?  What can we learn from  Do universal spatiotemporal 'rules' of dynamic behaviour exist for stocks, and if so could these be used in new types of simulation model, to more accurately forecast long-term policy impacts?
The first country to reproduce Colouring London's open code was Lebanon, with Coloring Beirut  set up in 2018 by the The American University of Beirut's Urban Lab, working with the National Center for Remote Sensing (CNRS) of the Conseil National de Recherche Scientifique (CNRS-Lebanon).
In early 2020 the University of Bahrain's Urban and Housing Lab began exploratory work on Colouring Bahrain, with a view to generating open data on the country's stock as a whole. Our partners in Bahrain and Lebanon are also working collaboratively to look at ways to support other research institutions in the Middle East wishing to develop Colouring City platforms.
 
We are also delighted to announce collaborations with The Leibniz Institute of Ecological Urban and Regional Development (IOER) in Germany, on Colouring Dresden, with the Cities Future Research Centre at the University of New South Wales, on Colouring Australia, and with the National Technical University of Athens, on Colouring Athens. 
CCRP partners can be identified by our Colouring Cities logo and their listing on this page. A dedicated CCRP website, providing a portal to CCRP partner projects is currently being built.
Please do contact us at the Alan Turing Institute if you are an academic research institution interested in setting up a Colouring Cities platform and would like further information on joining the CCRP.
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