Geoscience Reference
In-Depth Information
software packages such as ArcGIS. Menking and Stewart (2007), for example, reported taking stu-
dents into a field study area to teach them how to map river meanders using a tablet PC, with GPS
capability and stylus, running ArcGIS. Here, it is argued that the users were actually disadvantaged
by using a stylus-driven tablet PC, as the method of interaction between the user, the device and the
software did not afford being mobile. The authors went on to suggest that a more traditional method
such as handheld GPS data collection followed by a period of analysis out of the field (i.e. back at
base) would have been preferable, to their reported method, although they did acknowledge that the
users in such cases were unable to review and analyse their data in situ which is one of the things
that LBGC is attempting to allow for. It was also noted that interaction with a tablet computer using
a stylus under any troubling environmental conditions would be difficult due to the design of the
machines, screen glare and system failure. Battery life was reasonable for a short afternoon field
trip, but backup batteries were required for any longer period.
15.4.5 a
ugMented
r
eality
and
V
iSualiSation
As a set of technologies, AR offers opportunities to visualise information when performing LBGC.
AR is designed to incorporate the surroundings of the user with contextually relevant information
augmented on top of the natural world. On mobile devices, this usually means viewing information
on the device, layered over a camera preview image obtained from the device's camera, with the
position of the assets controlled by the device's sensors; the compass determines the translation of
the asset along the horizontal axis, the tilt sensor determines translation along the vertical axis, and
the size of the asset is controlled by distance to the asset's real-world location as calculated by the
device's position to the asset position.
Types of devices used for AR can vary from very simplistic pieces of acetate which can be held
up by the user over the real world to show different information present in the natural landscape
such as geology, to the mobile devices associated with LBGC (Priestnall and Polmear, 2007). For
LBGC, however, we wish to employ the power of computation with the know-how of researchers.
Therefore, in this section, we will discuss AR in terms of what is used on mobile devices. Delivering
AR on mobile devices requires five computational stages (Wagner and Schmalstieg, 2009):
•
Camera reading
•
Pose tracking
•
Network communication
•
App overhead
•
Rendering
From a technical perspective, these requirements can be met, meaning that it is possible to pro-
duce an AR app on mobile devices. However, making AR usable on mobile devices is far more
difficult, due to the unreliability of the sensors and the difficulty of holding the device with the
screen parallel to the user, in one hand, and attempting to interact with assets on screen whilst
moving around. One method of addressing interaction issues is to change the metaphor of the
touch screen. For example, picking out points accurately in the landscape using a touch screen is
problematic because of the difficulty involved in keeping the device steady with one hand whilst
selecting parts of the landscape with the other hand in order to place a point. Meek et al. (2013)
address such difficulties by changing the interaction method and making the device's interface
look like a camera, as users are more inclined to use it like a camera. A camera affords holding
the device still, picking what needs to be captured carefully and, importantly in this app, only
capturing what one can see.
However, user interaction and visual difficulties notwithstanding, AR technology has still
been employed to varying degrees in a number of mobile apps.
Environmental Detectives
is an
educational intervention where the students were given devices to investigate a simulated toxic
