IEEE Technology and Society Magazine - December 2015 - 34

of people, and other urban entities.
The collection of such data is used
to drive evidence-based decisions
for the provision of city services,
city governance, and the future of
physical and social forms [5]-[8].
Current investments in infrastructure, particularly ICT, are producing new urban and regional
environments. These generated
spaces in urban and suburban
areas are vastly different from our
previous experience, often regarded as digital urbanism [9]. For
example, the development of digital work hubs across South-East
Queensland, Australia, provides collaborative and networked workspaces by locating diverse activities in
suburban areas. Such an approach
holds promise in being able to
improve the vitality of small towns.
Information emerging for planners
and decision makers from ICT has
provided opportunities to enhance
their understanding of urban environments [10].
Toole et al. [11], for example,
used mobile phone data (call data
record) in Boston to investigate
how the real activity characteristics of each land use differs from
its regulated zoning. In another
example, the City of Portland in
the United States used a fitness
App as a planning tool to exploit
big data, identifying the optimal
solution for designing a path for
cyclists and improving road intersections [12]. The continuous type
and frequency of data informing
planners and decision makers,
therefore, are challenging conventional approaches that once relied
solely on authoritative historical government data collected in
discrete time intervals. Real-time
urban sensing, geo-tagged crowd
sourced data that support collaborative and multi-dimensional, multispatial urban models demand a
significant change from convention-

al urban planning and management
to a smart city planning approach.
Current statutory planning and
land administration systems, however, are unable to bring together all the various and disparate
sources of information [13]. To
date, planning and land administration organizations have been
tightly controlled by the regulatory process, which has limited new
and innovative approaches to planning [10]. This is one reason that
planning and land administration
systems are not fully exploited to
take advantage of the available
digital infrastructure to offer electronic services, and integrate interdisciplinary spatial data sources
[14] in the practice of governance
[15]. In addition, current planning measures suffer from a lack
of coordination and unintegrated
technologies that could be harmonized, carrying new opportunities to improve the realization of
urban quality of life. A fundamental
requirement for overcoming these
gaps is to redefine interdisciplinary
urban indicators, enabling planners
and decision makers to undertake a
holistic assessment of urban quality of life from a smart city planning
point of view.
The ISO international standards
organization developed a key standard ISO/DIS 37120 "Sustainable
development and resilience of communities-Indicators for city services and quality of life." ISO 37120
defines methodologies for a set of
such indicators, organized in 17
themes around social, economic,
and environmental development.
The aim of these interdisciplinary
indicators is to steer and measure
the performance of cities on providing services and quality of life. As
such, there is a great opportunity
for urban planners and land administration organizations to adopt the
interdisciplinary urban quality of
IEEE Technology and Society Magazine

life indicators for comparable and
verifiable decision making. The ISO
37120 indicators can act as drivers for the adoption of a smart city
planning approach, as they incorporate two key features:
1) The development and communication of data needed for most
of the ISO 37120 indicators
requires geospatial data as
smart technology [16].
2) Achieving
these
indicators
needs innovative tools enabling
the integration of geospatial
data and ICT-driven data.
Spatial information technologies, particularly geo-located sensors, are essential for developing
and communicating data required
for most of the ISO 37120 indicators [17]. For instance, the recreation category of ISO 37120 (clause
13) is divided in two indicators of
"square meters for indoor recreation space per capita" and "square
meters for outdoor recreation
space per capita" (clauses 13.1
and 13.2, respectively). Spatiallyenabled network sensors and technologies can generate such data
for indoor and outdoor spaces (i.e.,
satellite imagery, 3D cadastre, etc.)
[18]. Furthermore, for achieving
these indicators, spatial "flows" are
also important for understanding
recreational space [17]. Supporting indicators could be the number
of users of recreational space, the
means and times users access and
utilize these spaces, and demands
on environmental aspects such
as flows of energy, water use, and
waste production in a given space.
In addition, these spaces and their
spatio-temporal attributes are connected to neighboring or nearby
non-recreational areas. Urban planning and land development organizations will need this kind of
spatial and temporal information
to optimize and maximize benefits
for society.
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december 2015

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - December 2015