Geography Reference
In-Depth Information
provide data on a 50 km grid cell resolution), but also by the lack of information of
what the local changes may mean at the farm scale. For example, a farmer may
have great difficulty translating an increase in average annual temperatures of 2 C
in terms of crop yield or farm revenue. Consequently, even localised climate data
may not be sufficient, without further interpretation, to allow land managers to
relate to climate change and truly understand its potential implications on their
livelihood.
Three-dimensional (3D) photo-realistic visualisations have been principally
deployed in the urban planning context, to provide more substance to abstract
alternative scenarios by making data more concrete in the user's mind and
allowing him/her to better relate to it. For example, Hudson-Smith and Evans
(
2003
) modeled a virtual London using 3D Geographical Information Systems
(GIS) software.
Sheppard (
2005
) pioneered the use of such technology to explore future climate
change scenarios. Our approach (described below) aimed to make climate change
projection and impact data more relevant to local stakeholders by combining the
use of local climate data and model outputs with 3D photo-realistic visualisations
of how things currently look on the ground and how they may change under future
projected climate conditions. Such an approach has previously been used to rep-
resent likely agricultural responses to climate change in the United Kingdom
(Dockerty et al.
2005
). Our approach focused on a single case study farm in south-
western Victoria named Demo Dairy. We developed, on the Google Earth digital
globe platform, a 'virtual Demo Dairy' (
http://www.dpi.vic.gov.au/dpi/vro/
vrosite.nsf/pages/geovis_virtual_demoDAIRY
) in which local stakeholders could
visualise and access local data relevant to their industry.
This virtual farm was based on two components which were integrated into
Google
Earth
through
the
use
of
KML
functionalities
(balloon,
object
and
panorama):
• The first component provided access to general farm information and data on
pasture growth under different climate change conditions data (see
Sect. 2
).
• The second component made use of 3D photo-realistic image rendering soft-
ware, namely 3D Studio Max and Visual Nature Studio (VNS) to depict local
infrastructure and conditions on the ground as well as possible futures.
4.1 Providing Access to Local Data
One of the objectives of this research was to explore the use of a digital globe
approach for making climate change data and modeling products more accessible.
Our project made use of Google Earth placemarks: clickable point features to
which information can be associated (similar to that described in
Sect. 3.2
)to
embed information at chosen locations. The visualisation product developed
