download time, and 7 s versus 0.2 s for zoom and pan operations, highlight the
fact that dynamic querying has potential as an approach to managing larger data-
sets on smaller devices, but that further work is still required.
Keywords Scale dependent rendering • Performance • Mobile apps • 3D city
models • 3D country models
The use of three-dimensional (3D) City Models on mobile devices (such as
smart phones and tablets) underpins applications including utility infrastruc-
ture validation (“call-before-you-dig”), planning (Batty et al. 2001 ; Coors et al.
2009 ; He et al. 2012 ), augmented reality (Chen and Chen 2008 ), personalized
tourist information [Schulte and Coors 2008 in (Boguslawski et al. 2011 )], real
estate sales and 3D navigation (Basanow et al. 2008 ). Importantly, 3D datasets
are now making their way out of the research domain and into real-life usage.
For example, applications such as the identification of illegal residential build-
ings using heat sensing devices (Watson 2013 ) and the use of 3D mapping to
assist town planners with noise mapping (Robertson 2013 ) highlight the impor-
tance of having access to 3D data and being able to integrate the data with other
information provided in 2D, as well as display this information in a mobile
context to facilitate access when visiting the sites showing illegal dwellings or
The prevalence of these applications is growing with the increase in availabil-
ity of mobile devices—indeed, there are over 1.08 billion smartphones globally
(Alexander 2012 ) which compares with 1.2 billion personal computers (PCs).
More people access the web via a mobile device than via a computer (Fling 2009 ).
In addition (Fling 2009 ) describes the mobile device as the seventh mass medium,
following on from printing, recordings, cinema radio, TV and the internet. Mobile
devices are truly personal, always on and always carried (Fling 2009 ).
Extruding two-dimensional (2D) topographic mapping data to a given height
is an efficient method of creating the 3D datasets required for such applications,
in particular where coverage should be city wide and high level of detail—e.g.
roof structures - is not required. It results in flat-roofed buildings, takes advantage
of legacy investment in 2D topographic mapping and also has the benefit of inte-
grating 3D buildings with a 2D basemap (Kada 2009 ). Importantly, this approach
has the potential to generate 3D data beyond the boundaries of a city, perhaps at a
national level. The resulting 3D data is generally quite large in volume and com-
plex in detail (Glander and Dollner 2008 ) and thus potentially difficult to visualize
in its entirety, in particular on a mobile device. Additionally, the adequacy of 3D
detail, the visual impact of the resulting 3D dataset, the suitability of the response
times and the overall usability of the 3D model depends on the specific applica-
tion for which the 3D City model is to be used—i.e. the context of use (Kjeldskov