X04. London prototype. Reasons for choice of London - colouring-cities/manual GitHub Wiki

edited by polly64.

Selection of London as the prototype city, and system of interest Applying learning from microspatial colour maps

Application of learning from Turing team's previous work on London

London was selected as the system of interest in large part owing to Polly Hudson's previous work into the capital and its evolution. Relevant projects include: the generation of building age maps of Shoreditch for a London amenity society (1995); the design and set-up of The Building Exploratory in Hackney and its GIS platform (1996-2001); the Camden Age Map, with Louis Jobst and LB Camden below (2010); the coordination of research for the Smarter London exhibition (New London Architecture, 2014); the curation and design of the ‘Almost Lost exhibition’, for English Heritage, in which 2D, 3D and 4D digital approaches to visualising demolition and protection in London were experimented with (Hudson, 2013) and commission/ the direction and co-design of the Clapton 4D animation(2002-2014) and The London Evolution Animation (2012-14).

London as a city of global interest

London is the capital of both England and the UK, and is three times the size in population (measured by municipal boundary) of any other UK city (Elledge, 2015). Greater London is one of the nine regions that make up England (Office for National Statistics, 2021b). London therefore provides the opportunity to demonstrate the relevance of open building attribute data platforms at both city, and regional scale. London is also a city of global interest. Its attractiveness, and consequent development pressure placed on it, is reflected in its number one ranking on the 2020 Global Power City Index for ‘city magnetism’ (defined as the ability of a city to attract people, capital and enterprise) (Mori Memorial Foundation, 2020); its number three ranking on Mastercard’s most-visited-cities-in-the-world list (Mastercard, 2019) and its number two ranking on the Global Financial Centres Index of most important global financial centres (Long Finance, 2021). As such, high quality, granular, open spatial data on the composition, operation and dynamic behaviour of London’s stock is likely to have many applications, particularly where comparative analysis at the microscale, across major cities, is desired.

London as an example of a mature, industrial city

London has evolved over an exceptionally long period, of two millennia, and is a prime example of a mature industrialised city (Evans et al., 2017). Stanilov describes it as a ‘global city of unique historical significance’ owing to it being ‘the first modern metropolis of the industrial age’ (Stanilov, 2012, p. 29). Information on London’ historical development is therefore of particular relevance to those looking to analyse the impact of industrialisation over more than 200 years. Like other mature cities in Europe, London falls under Chavez et al.’s definition of the ‘built city’, described as ‘mostly stable’ in dynamic terms (Chavez et al., 2018). Here, both slow and fast dynamics coexist, generating a mixture of short and long building lifespans. The average age of buildings is high compared with other European cities (Hassler, 2009), with almost a third of domestic properties built before 1918 and over half built by 1940 (HM Revenue and Customs, 2018). Fast dynamics in London are well illustrated by the ongoing high level of construction and demolition occurring in the City of London, and slow dynamics by the protection of around 15% of London’s buildings by designation.

Availability of historical records

The development of London is recorded in ‘voluminous studies charting its growth’ (Stanilov and Batty, 2011, p. 258). As well as the availability of a vast array of books, articles and academic publications, London offers numerous free archives, libraries and online collections. An exceptional range and quality of maps of the city is also held in local, regional and national collections, discussed at the end of this chapter. These include examples of London’s tradition of colour-coded maps. Access to such resources is essential in the development of any platform designed to provide high quality age and lifespan data.

London tradition of Colour coded coded London maps

London during the 19th and 20th centuries was also the source of a number of initiatives, academic, commercial and government led, that produced beautiful, informative colour-coded maps of cities at building and sub-building level, from the late 19th century to the Second World War. These, as shown below included Booth’s poverty map showing wealth inequalities in London; the highly detailed Charles E. Goad insurance maps, containing information on heights, number of storeys, street width and land use, and colour-coding construction materials such as brick, glass and wood at sub-building level (Layers of London, 2021; British Library, 2021); 1930s maps of City of London providing information on height, land use and age; and London County Council’s Architect’s Department bomb damage maps, designed to aid reconstruction after the war (ranging from yellow for ‘windows blown’ to black for ‘total destruction’ [Ward, 2015]). In the bomb damage maps, the colour coding was considered so informative for future enemy targeting that government approval had to be gained for the production of all colour copies (ibid.).

Historic environment Sector ecosystem

London has also developed, over the last century, a sophisticated ecosystem of local, voluntary, amenity and civic societies, and preservation groups (Bayliss, 2010). These operate across the city, observe change to the stock at the building level, and explore ways of retaining uniqueness and extending building lifespans in local areas. Many local amenity societies in London were set up between the late 1950s and early 1970s, in response to large-demolition programmes after the Second World War (ibid.). They have been responsible, historically, for driving designation policy in London (Hudson, 2013). The first, founded in Camden in 1839, later known as the Society for the Protection of Ancient Buildings (SPAB), went on, as did the Victorian Society, the Georgian Group and the Twentieth Century Society, to become national amenity societies, dedicated to the preservation of specific building periods and types (Bayliss, 2010). Over one hundred London societies and groups are represented today by The London Forum of Amenity and Civic Societies (London Forum of Civic and Amenity Societies, 2021). This study argues that these organisations are critical to the development, quality and the sustainability of an open building attribute prototype for London. In Chapter 7 and 8 methods of creating expert feedback loops to allow these groups, and other historic environment experts, to check and enrich computationally generated data, are discussed and tested.

Relevant London research studies

London is also the subject of a number of relevant studies into the sustainable development and dynamic behaviour of the building stock. These include Stanilov and Batty’s on determinants of growth in London (see Chapter 4); Frank Brown’s on the underlying logic of form in medieval London, Torma et al’s. on adaptation within plots in suburban high streets, and Roumpani’s work on Procedural London (see Chapter 5); (see Chapter 5). Stanilov’s unique spatiotemporal database for the city, spanning over two hundred years, is also a resource of major current and future relevance. London is also one of the cities selected by Kimon Krenz on which to test spatial methods of tracking demolition using OSMM TOIDs. Developing a platform for London therefore offers opportunities to draw from, and build on, this body of research.

The London Building Stock Model (LBSM), was also recently built for the Greater London Authority by UCL Energy Institute as part of its 3DStock programme (Steadman et al., 2020; Evans et al., 2017). The model builds on Steve Evans’ work at CASA on the Virtual London model, in 2005, (with Andrew Hudson-Smith and Mike Batty), which was subsequently used by Steadman, Ian Hamilton, and Evans to study the relationship of energy use to built form, and in particular to volume, surface area and plan depth (Steadman et al, 2020). The LBSM is the most detailed and sophisticated model of London’s stock available, and operates as a 3D ‘digital twin’ able to be used in stock monitoring, simulation and analysis. It explores the complex relationship between premises (areas where activities take place), and buildings (ibid.), and provides energy and carbon data for the GLA (Greater London Authority, 2019c). It is built using many data types of relevance to open platforms. These include OSMM footprints and addresses; VOA non-domestic land use and floor area data; OS Height data; Environment Agency LiDAR data (used to infer 3D geometry and storeys); plot boundaries (derived from OS and from INSPIRE land parcel data); and data on structural systems, materials, roof types, and age (from the commercial company Geomni) (Steadman et al., 2020). Though access to the model, and to most of these data types within it is restricted, images showing spatial patterns of land use generated from it; data required to build it; and UCL Energy Institute’s in-depth knowledge of attribute relationships,are all drawn on in the development of Colouring London. Support in generation of large-scale open datasets on building height and adjacency has also been provided. The author also worked extremely closely with UCL Energy Institute, Roumpani, and Stanilov from the outside to ensure the platform was as relevant and useful as possible to their work (ibid.).