City Evolution - digital
About (Site under construction)
As London and other cities face increasingly stringent energy legislation, and growing pressure on infrastructure and natural reserves, the efficient use of urban resources becomes ever more critical.
However urban efficiency relies on a detailed knowledge of a city’s resources: How much/many do we have? How long will they last? Where are they located? At what rate are they being depleted? What will be the impact of loss and to what extent can they be renewed and which elements are the most valuable and why? Yet these questions are rarely asked about our largest, most important and most complex manmade resource, our building stock.
This site, run by The Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London. explores these questions and looks at the role spatial analysis, machine learning, community knowledge and historical spatial data have to play.
Understanding the physical makeup
of our cities
Why is there such a lack of detailed open data (metadata) available on the physical makeup of the UK's building stock - our most important and complex manmade resource? What types of data relating to the urban fabric are of most use to the greatest number of sectors? Why is the collection of this data so essential to the intelligent cities agenda?
Collecting, collating, visualising and analysing and releasing metadata
How can we demonstrate to Ordnance Survey that comprehensive open building footprint release is essential to collect, collate, analyse and visualise metadata? How can we also encourage the Valuation Office Agency to release its Property Details dataset ?
London Designations
Courtesy Historic England
Analysing morphological value
What patterns can we see once UK metadata is analysed? What does this tell us about the relationship between building morphology and energy use, capital value health, crime etc. How can we use this information to inform demolition and planning policy?
Reducing demolition and creating sustainable building stocks
How can we use building age, and historical spatial metadata, to assess and visualise
building lifespans, historical and current rates of demolition, and the location of change? How can this help to reduce construction wasteand material extraction, facilitate retrofitting,maximise building longevity and inform more sustainable building design?
Visualising demolition and renewal
What is the value of visualising long-term evolution patterns within cities and local areas? What examples exist?
