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Planners in the Future City: Using City Information Modelling to Support Planners as Market Actors

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Recently, Adams and Tiesdell (2010), Tewdwr-Jones (2012) and Batty (2013) have outlined the importance of information and intelligence in relation to the mediation and management of land, property and urban consumers in the future city. Traditionally, the challenge for urban planners was the generation of meaningful and timely information. Today, the urban planners’ challenge is no longer the timely generation of urban data, rather, it is in relation to how so much information can be exploited and integrated successfully into contemporary spatial planning and governance. The paper investigates this challenge through a commentary on two City Information Modelling (CIM) case studies at Northumbria University, UK. This commentary is grouped around four key themes, Accessibility and availability of data, accuracy and consistency of data, manageability of data and integration of data. It is also designed to provoke discussion in relation to the exploitation and improvement of data modelling and visualisation in the urban planning discipline and to contribute to the literature in related fields. The paper concludes that the production of information, its use and modelling, can empower urban planners as they mediate and contest state-market relations in the city. However, its use should be circumspect as data alone does not guarantee delivery of a sustainable urban future, rather, emphasis and future research should be placed upon interpretation and use of data.
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Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 79
Urban Planning (ISSN: 2183-7635)
2016, Volume 1, Issue 1, Pages 79-94
Doi: 10.17645/up.v1i1.556
Planners in the Future City: Using City Information Modelling to Support
Planners as Market Actors
Emine Mine Thompson *, Paul Greenhalgh, Kevin Muldoon-Smith, James Charlton and Michal Dolník
Department of Architecture and Built Environment, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK;
E-Mails: (E.M.T), (P.G.), (K.M.-S.), (J.C.), (M.D.)
* Corresponding author
Submitted: 11 January 2016 | Accepted: 1 March 2016 | Published: 29 March 2016
Recently, Adams and Tiesdell (2010), Tewdwr-Jones (2012) and Batty (2013) have outlined the importance of infor-
mation and intelligence in relation to the mediation and management of land, property and urban consumers in the fu-
ture city. Traditionally, the challenge for urban planners was the generation of meaningful and timely information. To-
day, the urban planners’ challenge is no longer the timely generation of urban data, rather, it is in relation to how so
much information can be exploited and integrated successfully into contemporary spatial planning and governance. The
paper investigates this challenge through a commentary on two City Information Modelling (CIM) case studies at
Northumbria University, UK. This commentary is grouped around four key themes, Accessibility and availability of data,
accuracy and consistency of data, manageability of data and integration of data. It is also designed to provoke discus-
sion in relation to the exploitation and improvement of data modelling and visualisation in the urban planning discipline
and to contribute to the literature in related fields. The paper concludes that the production of information, its use and
modelling, can empower urban planners as they mediate and contest state-market relations in the city. However, its
use should be circumspect as data alone does not guarantee delivery of a sustainable urban future, rather, emphasis
and future research should be placed upon interpretation and use of data.
city information modelling; future cities; GIS; market actors; market rich intelligence; smart cities; spatial planning;
urban planning
This article is part of the issue “Urban Forms and Future Cities”, edited by Luca D’Acci (Erasmus University Rotterdam, The
Netherlands), Tigran Haas (KTH Royal Institute of Technology, Sweden) and Ronita Bardhan (Indian Institute of Technology
Bombay, India).
© 2016 by the authors; licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attribu-
tion 4.0 International License (CC BY).
1. Introduction: Planning in the Future City
In order to reflect on the theme for this thematic issue,
Urban Forms and Future Cities, this paper focuses on
one of Adams and Tiesdell’s (2010) three recommend-
ed areas for capacity building in relation to the con-
temporary spatial planning process in the future city,
that of the need for market rich information and
knowledge. Justifying this focus, Adams and Tiesdell
(2010) argue that the generation and use of market
rich Information and knowledge can assist in the medi-
ation and management of land, property and urban
consumers in the future city. This is because in most
mature urban locations, urban development is fi-
nanced by the private sector, making the ability of spa-
tial planners to understand and influence property
markets and development processes a crucial test of
their effectiveness (Adams & Tiesdell, 2010, p. 188).
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 80
The paper analyses this situation through the lens of
two City information Modelling (CIM) projects in order
to consider:
How CIM can assist in the creation of market rich
information and knowledge.
The opportunities and challenges involved in this
potential relationship in the future city.
In this paper, future cities is a term used to imagine
what cities themselves will be like, how they will oper-
ate, what systems will orchestrate them and how they
will relate to their stakeholders (citizens, governments,
businesses, investors, and others), in the future (Moir,
Moonen, & Clark, 2014).
In this imagination of the future it is no longer
enough to think of the city as the sum of its land, build-
ings and infrastructure. The contemporary city should
be engaging directly with all of its users, in order to
understand and improve their lives. This is because;
physical spaces, systems and users are increasingly be-
coming part of Mitchell’s (1995) Soft City, emitting
large quantities of data in real time. Indeed, why
shouldn’t we focus in on this area? Graham (2004, p.
35) indicates that, over the past 8000 years, cities have
always been places where the processing of infor-
mation and the creation of knowledge have been con-
centrated. However, this does not mean that the
emergence and ubiquity of big data should be taken as
a panacea for planning in the future city. Rather, big
data provides the potential bedrock for new urban
knowledge when it is efficiently utilized.
Illustrating this situation, from the mid-2000s, in-
fluenced by Building Information Modelling (BIM) and
its success and promises for the construction industry,
the term City Information Modelling (CIM) or urban in-
formation modelling, came into common use (Beirão,
Duarte, Montenegro, & Gil, 2009; Duarte, Beirão, Mon-
tenegro, & Gil, 2012; Gil, Almeida, & Duarte, 2011; Gil
& Duarte, 2008; Hamilton et al., 2005; Khemlani, 2007).
The authors define CIM as a cross disciplinary, holistic
approach to the generation of spatial data models in
which the integration, application and visualisation of
city data is used to manage and mediate the demand
for land, property and environmental resources; the
aim being to balance multiple stakeholders’ needs in
order to achieve sustainable and liveable cities whereby
citizens play a major role in city governance. A simple
way of understanding CIM is the following: if the smart
city can be taken to mean the transference of the city
from the analogue age to the digital one, then CIM is
the practical application of this digital data in relation
to the management and planning of the future city in
collaboration with its citizens and stakeholders.
This paper does not attempt to illustrate a history
of the smart city (for a thorough appraisal of the recent
eruption in literature in relation to this debate see
Kitchin, 2014), instead it is enough to state that “the
smart city concept has been around since the 1990s,
but it is still a fairly new concept, evolving from, and in
tandem with, technological developments...and the
concepts and research areas of the ‘virtual city’, ‘wired
city’, ‘informational city’, ‘telecity’, ‘intelligent city’,
‘urban cybernetics’, and the ‘digital city’, all of which
reflects a technologically enhanced vision of a city”
(Thompson, 2015, p. 501).
The analysis in this paper is focused on two on-
going CIM projects in the Department of Architecture
and Built Environment at Northumbria University,
namely Geo-Visualising Commercial Real Estate Mar-
kets (GV-CREM) and Virtual NewcastleGateshead
(VNG). Collectively, these projects combine research in
4 specialist areas, City modelling and data (Thompson,
2015; Thompson & Greenhalgh, 2014; Thompson &
Horne, 2010) urban visualisation (Charlton, Giddings,
Thompson, & Peverett, 2015; Giddings, Charlton, &
Horne, 2011; Horne, Thompson, & Charlton, 2014) real
estate market modelling (Greenhalgh, 2008; Green-
halgh et al., 2003; Greenhalgh & King, 2010, 2013) ur-
ban finance and digital spatial preference modelling
(Muldoon-Smith et al., 2015; Muldoon-Smith & Green-
halgh, 2015) indicating the multi-disciplinary nature
and collaborative ethos at the heart of CIM. Taken to-
gether, the learning outcomes of these two projects
enable the authors to reflect upon the opportunities
and challenges involved in the generation of market
rich information and knowledge and help answer the
underlying research question in this paper:
How can City Information Modelling (CIM) help
planners to influence urban form and the future city?
The aim of this appraisal is not to critique the re-
spective projects and their methodologies (both have
strengths and weaknesses) but rather to better under-
stand how CIM can aid urban planning through the
generation of market rich information and knowledge.
These reflections are structured around four key
1. Accessibility and availability of data
2. Accuracy and consistency of data
3. Manageability of data
4. Integration of data
Each theme discusses the opportunities and challenges
faced by each project while the proceeding section re-
flects upon how deployment of CIM could be improved
in the UK through our attempts to integrate the re-
spective types of projects already introduced, into a
holistic City Information Model (CIM).
Throughout, the paper reflects upon the broader
concern of how urban planners can exploit the inher-
ent potential in CIM and the challenges they face in do-
ing so. The concluding section reflects upon the under-
lying research question and argues that CIM offers new
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 81
and enhanced opportunities for planners and other
professionals working in the urban environment. Par-
ticularly, in relation to the deployment of real time da-
ta into the analysis of the conditions in which key plan-
ning and resource allocation decisions are made and
the appreciation of the longer term impact of such de-
cisions. However, they should also proceed with cau-
tion because ubiquitous urban data isn’t a panacea for
urban problems, rather its application, through consid-
ered interpretation, is a useful tool for informing the
multi stakeholder spatial planning process.
Most of the reflection in this paper will take place in
relation to spatial planning in the UK with particular
emphasis on England, however the reflections and
conclusions in this paper will also have salience for the
devolved administrations and the international urban
planning audience because most mature urban loca-
tions face similar types of challenges in relation to the
generation, management and application of urban da-
ta. While the findings should also be useful to planners
in emerging cities in the developing world where an
understanding of the urban process will be beneficial.
2. Planning Intelligence
According to Clifford and Tewdwr-Jones (2013) urban
planning in England is increasingly defined by spatial
planning, taken to mean the strategic co-ordination
and inclusion of disparate policy directives and stake-
holder interests in contrast to traditional forms of
more static ‘land use’ and ‘town and country plan-
ning’ approaches. Yet, spatial plannings underlying
evidence base is still regularly founded on historical
methods of data generation and analysis. Yes, the
gathering of data and the use of current technology
has been an everyday working practice for planners
for decades; for example in the 1980s local govern-
ments in the US started applying IT, notionally to speed
up data processing but also to improve the delivery of
services and to potentially increase political participa-
tion (Guthrie & Dutton, 1992). Moreover, Booth (2003)
tells us that computers have been used in the English
tradition of Development Control since at least the
1970’s. However, in the main, technology has been
used for routine administrative tasks and gathering da-
ta, rather than as a means of managing and shaping
the built environment holistically.
Examples to the contrary do exist; (Batty, 1991,
1997, 2007; Batty & Xie, 1994; Baud, Scott, Pfeffer,
Sydenstricker-Neto, & Denis, 2014; Geertman, Ferreira
Jr, Goodspeed, & Stillwell, 2015; Gordon, Karacapilidis,
Voss, & Zauke, 1997; Laurini, 2002; Páez & Scott, 2005;
Shiode, 2000; Wu, He, & Gong, 2010; and many others)
researchers in transportation modelling, agent-based
modelling, GIS, public participation, urban morphology,
spatial analysis, and virtual cities, have been working in
these overlapping fields for several decades now. In-
deed, research has emanated from various outlets such
as Computers in Urban Planning and Urban Manage-
ment Conference (CUPUM), Urban Data Management
Symposium (UDMS), Journal of Urban Technology, and
Computer, Environments and Urban Systems Journal
and many more. Yet, in the UK we believe that exam-
ples of this work are the exception, rather than the
norm. Spatial planning in the UK finds itself in a state of
inertia increasingly cognisant of the potential, and need
for new data models (Adams & Tiesdell, 2010; Batty,
2013; Tewdwr-Jones, 2012) to inform strategic spatial
planning but still reliant on tried and tested practices of
strategy development and evidence gathering.
Illustrating this situation, Turley Planning Consul-
tancy (2015) recently surveyed 326 Local Planning Au-
thorities and found that 50% had an employment land
evidence base which pre-dated the publication of the
2012 National Planning Policy Framework (NPPF) which
is the most recent review of planning in England. Plan-
ning Policy Guidance published in 2014 even recom-
mends that ELR’s do not need to be carried out any-
more regularly than every 5 years, although they
should be updated more regularly to account for
changing circumstances. This means that in certain cir-
cumstances planning in England is quite literally con-
ducted through the rear view mirror (Turley Planning
Consultancy, 2015).
Exacerbating this situation it is quite common to
see a long process of plan-led strategy formulation,
traditionally through structure and unitary develop-
ment plans and more recently, regional spatial strate-
gies, local development frameworks and, laterally, local
plans and core strategies. Each document goes through
a long process of formulation and is underpinned by a
wide selection of underlying research exercises, such as
Employment Land Reviews (ELR) Strategic Housing
Market Assessments (SHMA) and Strategic Housing
Land Availability Assessments (SHLAA). However, many
of these documents, by the time they are adopted, are
years out of date. On one hand this is because of con-
tinuing macro and micro level socio-economic changes,
and on the other hand, the time taken for consultation
and revision and the ceaselessly changing nature of the
planning system in England (Clifford & Tewdwr-Jones,
2013) which leads to the requirement for continual re-
formulation before publication.
So, the challenge is to capture information re-
sources that have the capacity to inform urban plan-
ning in a timely and accurate fashion; in order to in-
form the strategy formulation process and to enable
planners to exert influence over the form and devel-
opment of the future city. The proceeding section dis-
cusses how CIM can fill this deficit in knowledge and
identifies the opportunities and challenges involved in
this relationship. Consistent with Adams and Tiesdell
(2010), we do not seek to contribute to the rich debate
in relation to spatial planning (see Clifford & Tewdwr-
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 82
Jones, 2013) for an account), rather, we seek to inves-
tigate how CIM can be used as a tool by urban plan-
ners, operating as market actors, to nourish the con-
text in which spatial planning takes place and to inform
strategic planning and resource allocation decisions.
3. The Projects
The first project, Geo-Visualising Commercial Real Es-
tate Markets (GV-CREM) has generated an experi-
mental multi-criteria urban real estate model which
seeks to understand the nature and vitality of commer-
cial real estate markets in England and Wales. Initial
modelling has focused on Newcastle upon Tyne (Tyne
and Wear), Leeds and Croydon, which exhibit large,
mature commercial real estate markets and offer the
potential for inter and intra-regional comparative anal-
ysis. The underlying data is non-geometric and rests
upon a GIS dataset comprising physical characteristics
of commercial and industrial floorspace, occupancy
status and rental value information. The database con-
tains approximately 5billion sq.ft .of floorspace data
(1bnsq.ft.of office, 1bn sq. ft. of retail and 3bnsq.ft.of
industrial space) and has its origins in the National
Summary Valuation Data Set and National Non Domes-
tic Rating Returns created by the Valuation Office
Agency (VOA). Taken together, these data sets repre-
sent an accurate picture of commercial and industrial
real estate stock in the UK (Katyoka & Wyatt, 2008).
The model is also capable of incorporating demand ap-
proximation information secured through internet
search activity. The data model is intelligent, can be
disaggregated to individual buildings or aggregated to
the metropolitan or functional economic area, and can
be visualised in both 2D and 3D (with potential for 4D
longitudinal analysis using time series data). The 3D
representation in Figure 1 demonstrates the utility of
this model, where the height of each tower indicates
the quantity of floorspace in each location and the col-
our denotes the relative value of that floorspace.
Figure 1. Topological representation of commercial real estate supply in Tyne and Wear.
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 83
Furthermore, the representations in Figure 2 indicate
the relative characteristics of commercial office space
in Croydon. In this representation Croydon has been
sub-divided into equal size grid squares. The dots indi-
cate the location of commercial office property while
each grid square has been scaled to indicate the rela-
tive quantity of commercial office space in each loca-
tion with the colour denoting the value of office space.
In response to the report from Turley Planning Con-
sultancy (2015) Project GE-VCREM has the ability to
provide up to date employment land data while it also
has the ability to inform more efficient land use plan-
ning and economic development strategy develop-
ment. Following the recent turn towards fiscal decen-
tralisation in England it also has the underlying ability
to monitor and understand the impact of business rate
retention and the contemporary performance of urban
finance initiatives and economic stimulus programmes
such as Tax Increment Financing and the continuing
evolution of Enterprise Zones. This is because the basic
data infrastructure of GV-CREM is founded on the Eng-
lish business rate system.
Finally, Figure 3 describes the spatial distribution of
potential office, retail and industrial occupier preference
in Leeds. The aim of this emerging project is to use in-
ternet search behaviour to approximate potential occu-
pier preference for office, retail and industrial floorspace
in Leeds (Muldoon-Smith et al., 2015). The intention is to
use these urban search signals in the future to analyse
the relationship between the location of office, retail
and industrial premises and where potential occupiers of
these types of commercial and industrial floorspace ac-
tually want to locate. This research has been developed
to expose potential mis-matches between where busi-
ness occupiers want to locate and the physical location
of office, retail and industrial business premises and in
order to help guide the location of new commercial and
industrial floorspace development.
The second project, Virtual Newcastle Gateshead
(VNG) (Figure 4) is geometric and has been designed to
visualise the urban fabric of neighbouring settlements
of Newcastle upon Tyne and Gateshead in the North
East of England. Initiated in 2008, in partnership with
the two local authorities, the project provides a defini-
tive, accurate, interactive city model that offers a cost
effective stakeholder communication tool and way of
understanding the wider implications of planning ap-
plications. VNG is; helping to streamline and increase
the transparency of the planning process, supporting a
number of research and enterprise activities, allowing
the University to engage with a number of local and
national external parties and public groups.
Both projects demonstrate the applicability of CIM
to contemporary spatial planning England. On top of
the perennial importance of ‘location, location, loca-
tion’ we now have ‘evidence, evidence, evidence’. Yet,
the design evolution of both projects has not been
straight forward, each project has been beset, to vary-
ing degrees, by issues of data accessibility and availabil-
ity, data accuracy and consistency, data manageability
and data integration. The following section explores
these issues and reflects on the challenges involved in
the integration CIM into the spatial planning practice to
inform future CIM development.
Figure 2. Relative scaling in Croydon.
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 84
Figure 3. Potential occupier preference in Leeds.
Figure 4. VNG model (central core area).
3.1. City Information Modelling: Opportunities and
3.1.1. Accessibility and Availability of Data
Making data available is one thing, doing this efficiently
is another entirely. In other words, how data is pub-
lished and its format informs its accessibility and future
usability for research and practical purposes. Illustrat-
ing this situation, project GV-CREM had considerable
difficulty accessing uniform information for its data-
base despite the UK Government’s commitment to
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 85
open data. Illustrating this situation, the VOA, charged
with creating the national summary valuation data set
every five years, only release information through its
internet based Agent Mode System. Immediately, this
would appear to be a positive situation, however, they
only release information through an individual heredit-
ament that is an individual parcel of property that is
available for rent. The hereditament can pertain to an
entire building or a in the case of office buildings,
which are traditionally subdivided for rental purposes,
a part of a building, for example a floor or suite. To put
this in perspective there are 1.8 million hereditaments
in England and Wales, if we place an approximate time
of 1 minute per view on each individual hereditament
in VOA agent mode, without sleep, it would take 4
years for one person to create an aggregated property
data base for England and Wales. The solution to this
issue was purchasing the information through universi-
ty funds, an option open to the authors but not one
that is readily available to smaller organisations and in-
dependent researchers.
Furthermore, the database also makes use of Na-
tional Non Domestic Rate Returns (NNDR) which is data
related to vacant commercial properties. Access to this
data is inconsistent, some local authorities publish it on
a quarterly basis via their websites, and some only re-
lease it through formal request while others refuse to
release it at all.
Similarly, creating a 3D city model can be a chal-
lenging task. Specialist companies use airborne acquisi-
tion and photogrammetry techniques to create these
3D city models. Considering the VNG project started in
2008 the accessibility to 3D data was rather limited and
expensive, preventing availability of this type of data to
smaller organisations and independent researchers.
During the initial years of creating VNG, there were ac-
cessibility issues. These issues were generally in rela-
tion to the different and sometimes incompatible IT
systems and software within and across these three
organisations and remote access and version control.
Encouragingly, advances in data collection techniques,
computer graphics cards, processing power and 3D re-
construction methods (Gröger & Plümer, 2012) have
enabled the capture, production, storage and visualisa-
tion of more complex models an achievable goal. With
new techniques and technologies increasing their
availability and speed of creation, virtual city models
similar to VNG are becoming more common. In fact,
Morton , Horne, Dalton, & Thompson (2012) have
identified over one thousand models worldwide.
However, the issues of accessibility and availability
identified in this section could be greatly assisted if
public data was open source by default, without re-
strictions on commercial use, and made available in
non-proprietary and open formats. This would be aided
by national, regional and local governments publishing
a list of the datasets that they do not publish as well as
the ones that that they do release. Clearly, the journey
toward quality open data is an on-going process. How-
ever, this debate should not only be in relation to gov-
ernment transparency, perhaps the onus should also
be on those involved in CIM and urban planning to
prove that releasing quality open data is a worthwhile
3.1.2. Accuracy and Consistency of Data
During the initial stages of project GV-CREM an early
decision was taken to omit Edinburgh and Birmingham
from the case study because the data that each local
authority provided was of such poor quality. Both of
these locations are significant omissions from the UK
case study, both containing mature commercial office
markets, and is a source of considerable frustration on
the researchers’ part. Furthermore, different locations
store and process their data in different ways and use
different data storage applications which results in sig-
nificant issues of consistency upon receipt of data in
terms of format and the consequent time taken to re-
fine data sets into a synthesis. This was particularly ev-
ident in the NNDR data set. The VOA data set was more
consistent in terms of format. However, the infor-
mation that was input into the VOA data set was incon-
sistent (especially in relation to address), reliant on the
individual valuation officer conducting a building as-
sessment, an issue also identified by Astbury and
Thurstain-Goodwin (2014).
The VOA summary data could be immediately im-
proved if each valuation office carried a GPS system
and logged the geo-coordinates for each hereditament
and building. This would counteract address infor-
mation inconsistency and enable the differentiation of
buildings with identical post codes. Furthermore, each
building should be given a unique property reference
number which can then be related to the underlying
billing account reference numbers and hereditament.
Currently, it is possible to subdivide a hereditament
based valuation into its constituents parts, however,
this facility would be exponentially more powerful if
this process could be applied to entire buildings.
Furthermore, as VNG is being developed to be used
within the urban planning process, confidence is re-
quired in relation to the degree of accuracy of the data.
A pilot study conducted by Horne (2009) compared the
accuracy of the current 3D data with the true urban
form, by comparing specific views from the model with
traditional photomontage and surveying techniques.
Undertaking this study proved that the accuracy of the
model satisfied planners from both councils (Figure 5).
3.1.3. Manageability of Data
This issue of data manageability rests on Garnter Ana-
lysts Doug Laney’s (2001) classic big data conundrums
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 86
Figure 5. Verification of accuracy of Virtual Newcastle Gateshead. Source: Horne, 2009.
of volume, variety and velocity (not to mention the
other two v’s veracity and validity). Firstly there is just
so much information that it is difficult to know where
to start or when to stop. Only a few years ago the frus-
tration was not being able to do enough, now it is pos-
sible to answer almost anything providing the volume
of information can be harnessed. Then there is variety,
perhaps the greatest challenge in CIM is the sheer
quantity of incompatible data sets which cannot be in-
tegrated without considerable re-engineering. The
consequence is the need for multiple software and
hardware solutions which operate at best in unhappy
compromise. The final issue is velocity, not only is
there a great deal of information produced, it is also
generated repetitively and increasingly in real time.
One of the key challenges for spatial planning will be to
harness this challenging potential as there is now real
scope for planning strategy, decision making and nego-
tiation to be evidenced in relative real time. Hitherto, it
has been common place for planning authorities to rely
on evidence collected sometimes decades ago. How-
ever, it is now possible for initiatives like Project GV-
CREM and the emerging research into digital search
preference signals to evidence and justify new strategic
employment land allocations and to support or defend
against new development proposals with contempo-
rary market intelligence.
To date, VNG has been delivered and managed as
set of “tiles” or city square areas that are stored in a
widely used 3D graphical format (DWG) to support the
managing and use of the 3D data. Within each tile a
naming and layering convention is used to allow dis-
tinction between roads, paths, vegetation, buildings
etc. This format is ideally suited to loading selected ar-
eas of the model and performing the required visuali-
sation and analysis tasks. However up until recently,
additional interoperability of the data beyond this vis-
ual assessment is limited. This initial format is not suit-
ed to many other forms of analysis that may require
bringing together data from several or all tiles, or the
integration of other urban information from external
databases. It is therefore the interoperability, rather
than its similarity to the real world which should be the
focus of such models moving forward (Bodum, Kjems,
Kolar, Ilsøe, & Overby, 2006).
3.1.4. Integration of Data
Perhaps the greatest challenge in relation to project
GV-CREM has been the problematic nature of data in-
tegration. Ideally, all data providers should use con-
sistent information database systems and all property
data sets should contain a common unique property
reference number (UPRN) with which to easily link data
sets. A constant frustration throughout the research
project is that there is a lot of information out there
that remains un(der)exploited because of the time re-
lated difficulty associated with linking them together.
For instance, the researchers would have liked to link
Environmental Performance Certificate Information
(EPC) data to the model and the National Land Use Da-
ta Base (NLUD). Although available to the public in non-
aggregated form (EPC), and in raw format (NLUD), each
assessment does not have a common identification
code. Furthermore, the respective floor space meas-
urement methods in the EPC data files did not appear
to be consistent with the standard measurement of net
internal area used by the VOA and NNDR systems.
Similar difficulties have been experienced with the
VNG project. Although the CAD based structure of VNG
and similar virtual city models are ideally suited for the
loading of selected areas of the model for performing
the required visualisation commonly associated with
such models, additional interoperability of the data be-
yond this visual assessment is limited. Authors have
highlighted a range of other applications that virtual
city models could be used for; tourism, pedestrian and
transport modelling, culture and heritage, environmen-
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 87
tal and energy simulations (Batty et al., 2000; Döllner,
Kolbe, Liecke, Sgouros, & Teichmann, 2006; Lange &
Bishop, 2005) however current attempts to expand the
application of virtual city model have been limited.
Where attempts have been made, there has been a
tendency for such models to be optimised for their in-
tended end purpose, which frequently results in con-
straining future potential applications and therefore
reducing the sustainability of the models created. The
research described by Charlton (2011) and Horne,
Thompson and Charlton (2014) demonstrated the in-
teroperability of virtual city data to be utilised analyti-
cal software tools to predict the performance and visu-
al impact of urban proposals, enabling designers and
planners to gain greater understanding of performance
prior to construction. However, the authors highlighted
how a fully integrated approach was currently limited
by the interoperability between certain selected soft-
ware applications and conclude that in its initial for-
mat, VNG is not suited to many other forms of analysis
that may require bringing together data from several
or all tiles, or the integration of other urban infor-
mation from external databases.
4. Discussion: Creating a City Information Model (CIM)
Digital capabilities of BIM, GIS, urban analysis, geo-
design, urban design, urban data science, city infor-
mation modelling and visualisation have the potential
to change approaches to spatial planning. This change
is arising partly because of the data infused solutions,
as in Smart City applications becoming prominent and
partly because requirements of holistic responses to
urban problems and moving away from producing an-
swers in silos.
The previous section discussed the opportunities
and challenges involved in two CIM projects. This sec-
tion explores the potential for both types of projects to
be combined in order to exploit the data driven attrib-
utes of projects GV-CREM and geometric properties of
VNG. The remainder of this section explores this situa-
tion through a pilot project conducted in the Depart-
ment of Architecture and Built Environment at North-
umbria University over the summer of 2015.
As more emphasis is put on the concept of the
smart city and benefits of integrating systems and da-
tasets in order to achieve holistic solutions, the in-
teroperability of VNG is focusing towards the incorpo-
ration of data into the geometrical representations. We
have seen evidence of this within the construction in-
dustry and the emergence of BIM. In this notion, digital
three-dimensional geometrical data is linked with rela-
tive information (material, dimensions, price, stress
load, etc.) in order to create a virtual building. This pro-
cess aids in the development, assessment, construction
and management of a building throughout its lifecycle.
Although this technology is often applied to single
buildings or a small group of buildings rather than city
models, current research does highlight the possibili-
ties of applying a BIM-based approach to support fu-
ture city modelling and management, by utilising GIS
(Döllner & Hagedorn, 2008; Gil et al.,2011; Gil, Beirão,
Moutenegro, & Dunantie, 2010; Hudson-Smith et al.,
2007; Laurini, 2002; Stojanovski, 2013; Thompson &
Horne, 2010; and many others). The proposed infor-
mation-rich virtual city models developed on a data-
base platform would contain geometric parameters,
alongside relevant city information to support the as-
sessment and visualisation of the datasets, which would
offer greater capabilities in managing, accessing and uti-
lising the advantages of the 3D geometrical data.
5. Data Infused Virtual City Model
A pilot project undertaken during spring of 2015 aimed
to examine the feasibility of the proposed approach in
relation to the smart cities agenda, the project aimed
to establish the capabilities to add spatial information
to the model and to utilise the model for analytical
purposes. In order to form the capabilities of the geo-
metrical data linking spatial information, the study fo-
cused to embed free and accessible datasets from the
Ordnance Survey initially.
The VNG model comprises several layers: buildings,
bridges, grass, roads, railroads, footpath, fences, walls,
terrain, and trees. The focus of the research was on
importing and utilising the buildings layer, due to its
complex geometry and relevance and experimenting in
attaching a variety of associated datasets. Therefore
bridges, railroads, fences, walls and trees layers were
excluded from the preliminary study and the grass,
roads, railroads, footpath and terrain layers were com-
bined to create a “new terrain” layer, before conver-
sion to a TIN (Triangulated Irregular Network), a digital
data structure used in GIS for the surface representa-
tion. The aim was to store the buildings as a MultiPatch
feature so that one record in the database corresponds
with one building. Unfortunately, the structure of the
VNG dataset did not allow for this aim to be fully real-
ised; due to the initial 3D modelling techniques used,
the individual buildings are not always defined as
standalone entities and in many cases they belong to a
block of buildings, therefore matching the address data
to a specific building became problematic.
Similarly, the research established that due to the
way VNG was modelled, the geometry of the buildings
had a number of defects; unnecessary polygons and
surfaces which were not closed. Although this is not a
barrier in the usage of the model itself for city visuali-
sation purposes, it impairs the performance of the 3D
experience. Despite a number of attempts to try and
resolve the aforementioned issues within the GIS soft-
ware, via more automated and scripted routes, a usea-
ble solution has yet to be achieved. As such, it was es-
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 88
tablished that a reasonable way to fix this problem is to
edit the geometry directly in CAD programme which of-
fers a more powerful set of editing tools. If similar
models are to be commonly used within GIS platforms
in the future, automated geometry cleaning must be
prioritised before importing into the GIS. However, by
deriving and embedding some basic geometrical in-
formation; height, elevation, area, etc. this experi-
mental project still achieved some impressive out-
comes in spatial-visual analysis terms such as skyline,
line of sight, construct sight lines, skyline barrier, sun-
shadow volume, etc. illustrated by Figure 6 (af).
From the Ordnance Survey, we utilized; wards, dis-
tricts and streets data types within the boundary of
VNG. By embedding this information within the context
of VNG, it became possible to query for example;
which ward certain building belongs to. By combining
this knowledge with the derived geometrical data
(height, elevation, etc.), it is possible to analyse which
building is the highest or lowest in a particular ward,
district or street.
This approach was sufficient for establishing the
scope of the proposed approach and highlights the
possibilities of what could be done with more and dif-
ferent types of data. For example rent and tax data
would make it possible to find out the most expensive
part of the city or a certain ward. With the recent rec-
ord breaking rain fall in UK, flood damage can be de-
termined by using the elevation of the buildings and
the height of water level before hand and preparations
can be done accordingly. VNG and similar virtual city
models clearly have a big potential if GIS approach is to
be adopted. Transferring the model to City GML format
and embedding spatial information can also produce
very useful outcomes. For example the resulting model
can serve as an exchange platform and would also
greatly extend the usage of the virtual city model.
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 89
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 90
Figure 6. VNG 3D model in GIS platform: (a) Terrain model, (b) VNG in shape file format, (c) Querying in VNG, (d) Skyline
analysis, (e) Sun-shadow volume, (f) Analysing roof types (flat etc.) and roof orientation.
This pilot study showed that although problematic, a
3D city model can be enriched with different data
types and the resulting new model can be utilized for a
variety of analysis that can be used within city planning
purposes. Whilst it should be acknowledged that this is
a limited experiment it is clear that VNG and other sim-
ilar virtual city model data sets can be more aligned to
the development of the “real” city, allowing both visual
and analytical assessment of the urban environment.
6. Conclusion
The underlying research question in this paper con-
templated how City Information Modelling (CIM) can
help planners to influence urban form and the future
city and the broader concern of how City Information
Modelling (CIM) can be used to help planners as market
actors understand and influence urban form and the fu-
ture city. The evidence and experiences presented in
this paper suggests that CIM can be used by Urban
Planners and academics to re-engage in urban devel-
opment as market actors. For instance the emerging
research into search preference signals indicates how
CIM can be used as a powerful tool to inform the tradi-
tional basis of assessing planning applications on ‘their
own merits’ in the UK and recognising and evidencing
‘other material considerations’ in local areas. Project
GV-CREM can be used to substantiate employment
premises reviews and allocations of employment land,
while Virtual City Models (such as VNG) can be used to
interrogate the situational detail of new planning ap-
plications. In doing so, CIM can be used to counteract
rapidly ageing planning documentation and to influ-
ence complex negotiations in relation to viability and
developer contributions through the Community Infra-
structure Levy (CIL) for example. The central projects
indicate how planners can use CIM to model and evi-
dence a better future, for instance by using search
preference data to situate new development where
occupiers want it. In contrast to the passive records of
employment land and premises take up evidenced in
traditional employment land studies.
Increasingly, neither state intervention, nor neo-
liberal market solutions are seen as satisfactory ap-
proaches to urban planning challenges. The former is
criticised for its managerial inefficiency (see Booth,
2003 for an appraisal of development control and its
latter day association with inefficiency) while the latter
is criticised for its neglect of external and community
interests. Drawing on behavioural and institutional
theories of economics and property markets, Adams
and Tiesdell (2010) have put forward the argument of
planners as ‘market actors’ where planning practition-
ers operate confidently within state-market relations.
CIM offers an opportunity to answer their call for
greater market-rich information and knowledge, how-
ever, greater access to information does not automati-
cally mean that planners hold all of the cards, nor
should they. Rather, through the development and uti-
lisation of CIM, local planners can play a hands-on role
in evidencing and aiding urban change by providing in-
formation in relation to potential occupier demand, lo-
cal infrastructure provision and current land and prop-
erty availability. This would go some way toward
developing a planning intelligence tool which could be
used pro-actively in collaboration with the various ur-
ban development industries
Summarising our recommendations in the previous
sections, we call for a research focus into CIM and the
future city around the four key themes that structure
this paper. Across the world many cities now have
Open Data access sites where a variety of city related
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 91
data can be downloaded by anyone. Research com-
pleted in early 2015 shows that, 159 cities in 30 coun-
tries across the world have one or more open data ac-
cess sites. As well as these countries that have city
level open data sites another 32 countries have coun-
try level open data sites (Thompson, 2015). Illustrating
this situation, building and digital terrain models of
Berlin can be downloaded for free since 2013. Similar-
ly, geocoded national address data will be made openly
available from February 2016 in Australia. These devel-
opments show the potential of open data availability.
Yet, there is much more to be done before urban plan-
ners can fully utilise the full potential of “urban big da-
ta” and CIM in spatial planning.
Therefore, firstly, new research and scrutiny must
take place in relation to the accessibility and availabil-
ity of data in the UK. Secondly, it is imperative that
steps are taken to improve the accuracy and consisten-
cy of data. Thirdly, there is clear and present need for
research into the manageability of urban data, particu-
larly in relation to its volume, variety and velocity but
also its validity and veracity. Within the latter two
points, validity and veracity, resides a wider issue of
data ethics in relation to the massive amounts of data,
often personal, that is integrated into CIM platforms. In
particular the trade offs and f(r)ictions involved in se-
curing the future city through richer urban data and
the security and personal integrity of the millions of in-
dividuals who volunteer their data, either directly or
passively (Marvin et al, 2016). Finally, the ability to in-
tegrate urban data is of significant importance. New
research must take place into common unique data
referencing systems. The Unique Property Reference
Numbering (UPRN) system is gaining ascendency in the
UK; however, many datasets still do not carry this
number. The difficulty outlined in the previous section,
involving the merging of project GV-CREM and VNG,
demonstrates this complication and the frustration in-
volved in this situation.
Increasingly, both ‘big’ and ‘small’ data demands
complex systems of storage and analysis. It is no longer
enough to assume that data can be stored on a hard
drive: distributed systems and the Cloud are increas-
ingly the order of the day while increasingly complex
data algorithms are being designed to understand the
disparate nature of data. Therefore, the pressing chal-
lenge is to understand how these CIM opportunities and
challenges can be brought to bear on the spatial plan-
ning pursuit in order to evidence and manage the in-
creasingly complex and disparate nature of urban form.
Central to this concern is the acknowledgement
that the use of CIM should be circumspect as more da-
ta and intelligence alone does not guarantee delivery
of a sustainable urban future. Rather, emphasis, and
future research, should be placed upon how new mar-
ket rich intelligence is turned into knowledge through
interpretation and use of data. This is because, amidst
so much information, there is a risk that big data will
provide planners with ‘all of the answers’ which echoes
the unitary master planning tradition in the 1960’s
which was criticised for its totalitarianism. Consequent-
ly, CIM should be approached critically as a tool, rather
than as a means of cursory confirmation. Certainly,
new opportunities for real time information are seduc-
tive but they do not necessarily solve the problems set
out earlier in the paper in relation to old data. Rather,
the use of CIM provides planers with a new lens for
understanding and influencing the perennial challenge
of what the city should be.
The authors would like to acknowledge the contribu-
tions of Professor Steve Lockley, Professor of Building
Modelling, and Martin Cerny, Senior Research Assis-
tant, at Northumbria University
Conflict of Interests
There are no conflicts of interest.
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About the Authors
Dr. Emine Mine Thompson
Emine Mine Thompson is senior lecturer in Visualisation and Programme Leader of MSc Future Cities
programme at Northumbria University. Her research and teaching interests revolve around visualisa-
tion, virtual city modelling, smart/future cities and technologies such as augmented reality, VR and
BIM. Recently she led a visualisation project which was part of the Future of Cities Foresight Project.
She is a council member of eCAADe and a member of Northumbria University's Virtual Reality and
Visualisation Group (VRV).
Urban Planning, 2016, Volume 1, Issue 1, Pages 79-94 94
Dr. Paul Greenhalgh
Paul Greenhalgh MRICS is a Reader in Real Estate Economics, Faculty Director of Research Ethics and
Founder of the URB@NE Research Group and R3intelligence Consultancy. He is widely published in
the field of Urban Policy evaluation and the spatial analysis of commercial real estate markets. Paul’s
recent research investigates the implications of Government changes to the Business Rates System in
England and the spatial modelling of their potential impact.
Dr. Kevin Muldoon-Smith
Kevin Muldoon-Smith is a Research Consultant and Associate Lecturer at Northumbria University. He
is co-founder of R3intelligence consultancy specialising in property market information and research.
His expertise exists at the interface of real estate development, finance and public policy in which he
is widely published in academic and professional circles. His current research and consultancy pro-
jects are in two main areas: first, the impact of government policy on real estate and public finances
in the UK; second, the use of big data to model urban real estate stock characteristics and occupier
search behaviour.
Dr. James Charlton
James Charlton is a lecturer in Architecture at Northumbria University and a member of the Universi-
ty's Virtual Reality and Visualisation Group (VRV). Following his completion of his PhD in 2011, fo-
cused on the interoperability and application of virtual city models and performance software in the
design of city centre squares, James’ professional activities have continued to focus on the use of dig-
ital tools to support design communication and evaluation within architecture and urban design.
Michal Dolnik
Michal Dolnik studied GIS/Geomatics at Brno University of Technology, in the Czech Republic, during
which he spent atteneded the Geoinformation and Geomatics programme at the Technische Univer-
sität Wien in Vienna and spent an internship with the VirtualNewcastleGateshead (VNG) Project
Northumbria University. Michal’s other work experience includes participation in smart City projects,
conversion of 3D CityGML data to 3D GIS, data processing and collection from sensor network and as
a developer of GIS web-based applications.
... Through the CIM, urban planners and designers can work better on approaches such as traffic congestion, accessibility, and the potential impact of natural disasters. Because the CIM allows supporting the search for more information regarding citizens' potential demand and supply benefits not only for governance but also for the private entity, being able to provide preference data to locate a new venture where the occupants want it [4]. Provide valuable information for city governments, as well as citizens, through applications such as transport navigation, emergency response, and other location-based services [5]. ...
... Sustainable cities can be achieved through the use of CIM [1,4,7]. Thompson et al. [4] revealed that the multidisciplinary and holistic approach of CIM is what allows achieving sustainability because in this ...
... Sustainable cities can be achieved through the use of CIM [1,4,7]. Thompson et al. [4] revealed that the multidisciplinary and holistic approach of CIM is what allows achieving sustainability because in this ...
The growing demand of the population has caused serious problems for cities and has become one of the main challenges for city managers. This demand has occurred much faster than the tooling of public management. In this context, the urgent need for implementations that meet current requirements highlighting the advantages of City Information Modelling (CIM). The CIM helps in the search for information on future demands, providing a holistic view of the city. However, the absence of a full application and an established concept has been observed in the literature. Considering this, a systematic literature review and bibliometric analysis was conducted, resulting in 80 articles that composed the final analysis. We identified five recurring topics in the articles, the most important of the CIM, and discussed them in depth. We found a direction towards the CIM concept: the integration of Building Information Modelling (BIM), geographic information system (GIS), and a complete and up-to-date urban database, which enables analysis and simulation. The research concluded that a major effort will still be needed to establish the CIM, and its full implementation also depends on the dissemination of knowledge and demonstration of the tool's potential.
... • Lack of a framework and strategy for implementation. Currently, the application of CIM in CWM is still in its infancy, and as such it lacks a comprehensive and strategic framework for theoretical guidance [61]; • Interoperability of CIM. CIM is impeded by fragmented collaboration, which leads to incoherent and disjointed information due to the complexity of the data exchange between the information modeling software and projects [62]. ...
... Therefore, the data need to be kept unaltered during the transmission process to create a CIM environment that facilitates business collaboration; • Poor model quality and information asymmetry. There is an information gap in CWM, and the exchange of information between stakeholders is hindered, which has led to the predominance of waste disposal in landfills [63]; • Data availability, accuracy, and manageability [61]. The accuracy and manageability of construction data is a significant challenge [64]. ...
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Despite the large quantities of secondary materials flowing within the built environment, their actual volume and respective waste management processes are not accurately known and recorded. Consequently, various sustainability and material efficiency policies are not supported by accurate data and information-reporting associated with secondary materials’ availability and sourcing. Many recent studies have shown that the integration of digital technologies such as city information management (CIM), building information modeling (BIM), and blockchain have the potential to enhance construction waste management (CWM) by classifying recycled materials and creating value from waste. However, there is insufficient guidance to address the challenges during the process of CWM. Therefore, the research reported in this paper aims to develop a blockchain-enhanced construction waste information management conceptual framework (BeCW). This paper is the first attempt to apply the strengths of integrated information-management modeling with blockchain to optimize the process of CWM, which includes a WasteChain for providing a unified and trustworthy credit system for evaluating construction-waste-recyclability to stakeholders. This is enabled through the use of blockchain and self-executing smart contracts to clarify the responsibility and ownership of the relevant stakeholders. As a result, this study provides a unified and explicit framework for referencing which quantifies the value-contribution of stakeholders to waste-recovery and the optimization of secondary construction materials for reuse and recycling. It also addresses the issue of sustainable CWM through information exchange at four levels: user, application, service, and infrastructure data levels.
... The future state of the city is one of the major concerns on the minds of decision-makers and professionals involved in city planning (Kresl, 2007;Raven et al., 2018;Thompson, Greenhalgh, Muldoon-Smith, Charlton & Dolník, 2016). It is important for planning professionals to make necessary plans and deploy necessary tools in readiness for the future, if they are supporting resilient and -most importantly -sustainable development (Schubert, 2019;Fan, Weng & Wang, 2007). ...
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Projections and predictions of urban growth provide information that can lead to a certain level of preparedness for making cities resilient and sustainable. To ascertain the degree of confidence in predicting urban growth, this paper back-tests the Cellular Automata (CA)-Markov Prediction Model (PM) by comparing the results of the model for 2010 and 2020 with the actual land-use patterns and growth of Isparta for the same years. The data used are Landsat images for 1990, 2000, 2010, and 2020. The images were classified and used to perform the CA-Markov PM. The findings show that successive changes in land use in Isparta display average proximity to the CA-Markov PM results, with strong positive correlations of 0.8559 in 2010 and 0.8494 in 2020. It is therefore attested that amongst other models the CA-Markov PM can be used as a mathematical model for simulating urban growth in Isparta.
... Indeed, as Dall'O et al. (2020) state, urban planning becomes more complex because of the fast-paced evolution of urban spaces, the services offered by a given city as well as the city inhabitants' needs. According to this perspective, several authors consider CIM as a suitable platform to support urban analysis processes aiming at better sustainability and integration of information (Amorim, 2015;Billen et al, 2015;Correa and Santos, 2015;Amorim, 2016;Thompson et al, 2016;Almeida and Andrade, 2018;Dantas et al, 2019;Petrova-Antonova and Ilieva, 2019;Sielker and Sichel, 2019). ...
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Urban planning is a very complex task, especially considering the many challenges it faces, including an increasing need for housing in response to demographic growth and a need to limit abusive land artificialisation. As part of an interdisciplinary action-research project focused on experimenting with various uses of an existing City Information Model (CIM) for urban design, we are developing a new indicator to characterize urban intensity and a method to quantify it through the City Information Model (CIM) of a French eco-district. Our project is ongoing, and, in this paper, we present intermediate results on the potential of this CIM to support the automated quantification of our urban intensity indicator. We also describe the solutions currently implemented so that our experimental CIM can provide the necessary information for a more complete and automated urban intensity analysis. Finally, we shed light on key issues regarding the use of CIM, specifically CIM made up of various BIM models (of buildings lots and public spaces) for urban analysis at the district scale during the design phase. These issues include the need to generalize BIM entities and to manage property sets and nomenclatures to allow automation of analyses at the district scale, as long as there is no BIM+ data model allowing for urban analysis.
... An interdisciplinary, holistic approach for the generation of spatial data models. CIM models integrate, apply and visualise city data to enable the management and mediation of the demand for land, property and environmental resources (Thompson et al. 2016). ...
... Studies on CIM have advanced in the past decade; initial works described cities as street systems (Beirão et al., 2009b), followed by the establishment of the concept and profound debates on its structure and applications, as seen in Gil (2018), Beirão et al., (2015), and Thompson et al. (2016). Later work described the encoding standard for CIM (OGC, 2012) and actual cities such as Helsinki using CIM as a management tool (Higgins, 2017). ...
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This study developed a descriptive 3D city information model (CIM) using only infrastructural building modeling tools to create maps and analyzed the model according to needs identified in interviews with public-sector actors and a bibliometric analysis. The interviews assessed the challenges of implementing CIM in the Brazilian city of Curitiba, while the literature study determined that current academic production reflects the current reality, calling attention to relevant issues. The experimental software solution successfully created 3D informational modeling of cities for passive use as well as maps to support decision making, although it did not offer advanced parametric tools for urban analysis. Still, this model provides a flexible approach to overcoming the challenges reported by interviewees, which included financial limitations and organizational culture.
Conference Paper
Today, the tasks of managing the stages of the life cycle of capital construction projects in Russia are becoming relevant due to a number of changes in the regulatory, technical and regulatory documents. The article deals with the problem of consolidating the activities of all participants in the stages of the life cycle of an object - research, design, construction, operation. The purpose of the work is to identify the key parameters that affect each stage of the building cycle efficiency and control them. The article presents the results of the analysis of Russian and international scientists on the research topic. The research methodology is built using the methods of system analysis, construction systems engineering, methods of mathematical statistics. The parameters influencing the state of the system with regard to the stages of the project life cycle, including justification of investments, engineering surveys, architectural and construction as well as organizational and technological design, and construction are identified. The results of the analysis of the stages of operation, reconstruction, modernization, overhaul, restoration, decommissioning, demolition and disposal of the project will be presented in detail in further research.
The concept of city information modeling (CIM) has become increasingly popular in recent years. A literature review of previous CIM studies is presented in this paper. First, a bibliometric analysis of the current global CIM research is described, revealing that CIM has become a significant research hotspot. Next, three main research areas of the current CIM technique, namely data collection, integration, and visualization, are summarized to describe the characteristics of CIM research. Furthermore, some widely used CIM platforms are compared, and typical application cases of the CIM technique at different stages of the city life cycle are summarized. Finally, the current issues in CIM research are discussed, and future development directions are proposed. The findings of this study are expected to help researchers understand the current state of CIM and identify future development directions, thereby promoting CIM research development.
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The urban theory is voluminous body of knowledge. There is a kaleidoscope of urban definitions and standpoints, but there are no tools that capture the variegated viewpoints and representations in urbanism. In this article I look at different urban theories, discourses and representations in architecture, sociology, geography, economy, transportation, computer science in order to conceptualize city information modeling (CIM). CIM is conceived and discussed as a system of blocks with dynamic relations or connections that define and redefine territories. The urban life today is a sequence of temporally inhabited and interconnected spaces, movable or fixed. The connections between spaces inspire or inhibit contacts and interactions between people. They bend times and continuously shape and reshape spaces, sociabilities and situations. In architecture there was an evolution from computer-aided design (CAD) to building information modeling (BIM), but in urbanism, where the geographic information systems (GIS) dominate, there is no such analogy.
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In an era of continuing Local Government austerity and enhanced urban financialisation, Local Government in England is increasingly reliant upon decentralised methods of urban finance (typically based on ‘new economic growth’ extracted from non-residential property development) to fund public services, economic development and urban regeneration. Opportunities for greater territorial governance and economic development often frame fiscal decentralisation, yet, critical appraisals of this agenda are less common. Reflecting upon this issue, this paper critically appraises the underlying method of ‘localist’ finance in England, the Business Rate Retention Scheme. In doing so, it describes a picture of geographical variegation in England, one that suggests that the Business Rate Retention Scheme could lead to splintered urban development, based on the necessity (and underlying viability) for new development. The paper concludes that a minority of ‘premium locations’, characterised by buoyant property market characteristics, could outperform more numerous ‘stranded’ and ‘redundant locations’. The result is that those areas most in need of investment, that exhibit some kind of market failure and geographical disadvantage, could be less able to generate new development in order to fund the Business Rate Retention Scheme. Under these conditions, rather than correcting incidences of spatial inequality, fiscal decentralisation could further polarise uneven development.
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Since their emergence, digital information and communication technologies (ICTs) have been applied in many urban planning and management contexts. Not only do they have the capability for collecting, managing, analysing and storing information about cities more efficiently than ever before, but new technologies also present planners and managers with opportunities to draw on this information to improve city life.
Traditionally, urban analysis has been quick to adopt and benefit from developments in technology (e.g., microcomputer, GIS) and techniques (e.g., statistics, mathematical programming). This has not been the case, however, with newer methods of spatial analysis — in particular, spatial statistics. Only recently has this situation started to change. This paper documents the confluence of spatial statistics and urban analysis by first reviewing developments in spatial statistics, and then presenting examples of recent applications in urban analysis. The developments reviewed fall under the rubric of global and local forms of spatial analysis, and cover three major technical issues: spatial association, spatial heterogeneity and the modifiable areal unit problem. The examples highlight the relevance and usefulness of the techniques reviewed for urban transportation and land-use applications. The paper concludes with conjectures concerning future developments at the intersection of spatial statistics and urban analysis.
Since the turn of the 21st century, there has been a greater pace of reform to planning in Britain than at any other time. As a public sector activity, planning has also been impacted heavily by the wider changes in the way we are governed. Yet whilst such reform has been extensively commented upon within academia, few have empirically explored how these changes are manifesting themselves in planning practice. This book aims to understand how both specific planning and broader public sector reforms have been experienced and understood by chartered town planners working in local authorities across Great Britain. After setting out the reform context, successive chapters then map responses across the profession to the implementation of spatial planning, to targets, to public participation and to the idea of a ‘customer-focused’ planning, and to attempts to change the culture of planning. Each chapter outlines the reaction by the profession to reforms promoted by successive central and devolved governments over the last decade, before considering the broader issues of what this tells us about how modernisation is rolled-out by frontline public servants. This accessible book fills a gap in the market and makes ideal reading for students and researchers interested in the UK planning system.
Smart Urbanism (SU) - the rebuilding of cities through the integration of digital technologies with buildings, neighbourhoods, networked infrastructures and people - is being represented as a unique emerging 'solution' to the majority of problems faced by cities today. SU discourses, enacted by technology companies, national governments and supranational agencies alike, claim a supremacy of urban digital technologies for managing and controlling infrastructures, achieving greater effectiveness in managing service demand and reducing carbon emissions, developing greater social interaction and community networks, providing new services around health and social care etc. Smart urbanism is being represented as the response to almost every facet of the contemporary urban question. This book explores this common conception of the problematic of smart urbanism and critically address what new capabilities are being created by whom and with what exclusions; how these are being developed - and contested; where is this happening both within and between cities; and, with what sorts of social and material consequences. The aim of the book is to identify and convene a currently fragmented and disconnected group of researchers, commentators, developers and users from both within and outside the mainstream SU discourse, including several of those that adopt a more critical perspective, to assess 'what' problems of the city smartness can address. The volume provides the first internationally comparative assessment of SU in cities of the global north and south, critically evaluates whether current visions of SU are able to achieve their potential; and then identifies alternative trajectories for SU that hold radical promise for reshaping cities. © 2016 Simon Marvin, Andrés Luque-Ayala and Colin McFarlane. All rights reserved.
The British system of universal development control celebrated its 50th anniversary in 1997. Remarkably, the system has survived more or less intact but the experience of the 1980s has left large questions unanswered about the relevance and effectiveness of the system. This book traces the history of the development control system in Britain from early modern times to the present day.
In this paper we describe how urban data from different system and application domains such as Computer Aided Design (CAD), Geographic Information Systems (GIS), and Building Information Models (BIM) can be integrated by a service-based virtual 3D city model system. The 3D viewer client allows users to access, to import, and to integrate semantic-enhanced information models from the CAD, GIS, and BIM domain that are provided within a service-based geodata infrastructure. The 3D viewer client represents the core component that implements a number of adaptors for various OGC web service types, manages the resulting virtual 3D city model based on CityGML, and can act itself as a higher-level service delivering integrated information. This approach shows how urban data from different scales, different domains, and different shareholders can be seamlessly integrated at visualization level and how corresponding services can be setup. The work is based on our development of an interoperable 3D viewer client within the CAD/GIS/BIM thread of the Web Services Initiative Phase 4 of the Open Geospatial Consortium.
This study is a quantitative investigation into the retail markets of England and Wales between 2005 and 2010. We examine the performance of retail over space and time with particular reference to town centre activity and the impact of large off-centre retail, over a period of economic recession. We also estimate the relative income generated for Local Authorities by town-centre or off-centre location, to propound market significance by geography. Despite a widespread discussion of the impact of de-centralised planning over more than 30 years there have been no detailed studies quantifying this impact; the results aim to address a gap in current empirical evidence at the national extent. We use Valuation Office Agency (VOA) business rates as a proxy performance measure and geo-statistically defined town centre boundaries to create a nationally and statistically consistent methodology. The variation of business ‘rateable values’ is in part a facet of economic performance, and spatial analysis using Geographic Information Systems (GIS) allowed us to illustrate those areas over and under-performing the national economic market over the same period. New off-centre large retail developments were identified over the same time frame, to identify any correlations between new developments and the resilience of proximate town centres. The study highlighted multi-scale forces and patterns of impact and found a relationship between the proximity of new off-cenre large retail developments and retail floor space value change over time in town centres.
The increasing development of three-dimensional virtual city models and leadingedge computer software applications is providing innovative possibilities for analyzing the performance of existing city-centre public squares. In the design and assessment of city squares, the use of accurate virtual city models is often limited to visual geometrical assessment alone. There is little evidence that such models are being adapted to carry out urban performance simulations. There are, however, existing and emerging tools that can simulate a number of performance aspects—pedestrian movement, noise level, wind movement, and temperature—that show scope for integrating virtual city models to aid in the assessment of public squares. This paper describes a study which investigates the interoperability of off-the-shelf three-dimensional virtual city models to integrate with selected ‘urban performance’ software to contribute to a more integrated approach to the assessment of existing public squares and the future sustainability of virtual city models. Methodologies for utilising virtual city models within ‘urban performance’ software are established, with results demonstrating that the integration of virtual city model data can aid in both the visual and performance assessment of existing public squares, with scope for application to new proposals. The argument is also made that the application of virtual city models in this manner also contributes towards the sustainability of virtual city models, one that takes a more multifunctional approach. This paper acknowledges that the majority of the evaluated software is not related directly to urban design—indeed, there is no software currently available that brings together all the performance aspects and relates them to geometrical characteristics. However, this study offers a significant contribution to this subject and identifies the need for future research into the evolution of information-rich virtual city models.