International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004
programmed from scratch, which is beyond the current
capabilities of the research group.
7. CONCLUSIONS AND FUTURE DIRECTIONS
It is clear that there are a number of areas ripe for research in
this field, beginning with the definition of uncertainty as it
relates to visualised landscapes, moving through the technical
feasibility of the various options for representing it (which will
need to be revisited as technology develops), to the perceptions
and understanding of various groups of end-users when faced
with such visualisations. The first of these is vital if subsequent
work is to be carried out within a valid context, and to a large
extent will influence the sorts of images produced for
investigation.
It would seem sensible to begin with easily-modified still
visualisations in order to keep processing time to a minimum as
viewers’ perceptions are explored. By employing qualitative as
well as quantitative research methods, further insight and ideas
could be obtained from respondents; ideally such results would
be used to inform and direct research into more complex
animated or interactive methods. To these ends, the next steps
of this project will be to carry out preliminary surveys of non-
expert respondents to elicit their responses to these and other
simple expressions of uncertainty in visualised landscapes.
The eventual aim of this research is to feed back into the
visualisation process as it is used in real-life applications. In
helping visualisation producers to illustrate uncertainty in the
clearest and most accessible way, this work has the potential to
improve the communication of landscape-related information
and thereby enhance the environmental decision-making
process.
REFERENCES
3DNature, 2004. Visual Nature Studio.
http://www.3dnature.com (accessed 26" April 2004).
Appleton, K., and Lovett, A., in press. Computer visualisation
of planning proposals - comments from local authority planners.
Computers, Environment and Urban Systems.
Appleton, K., and Lovett, A., 2003. GIS-based visualisation of
rural landscapes: defining 'sufficient' realism for environmental
decision-making. Landscape & Urban Planning, 65 (3), pp.
117-131.
Atkinson, P. M., Foody, G. M., 2002. Uncertainty in remote
sensing and GIS: fundamentals. In: Foody, G. M., Atkinson, P.
M., (Eds.) Uncertainty in Remote Sensing and GIS. Chichester,
Wiley.
Craig, W. J., Harris, T. M. and Weiner, D., 2002. Community
Participation and Geographic Information Systems. London,
Taylor and Francis.
Couclelis, H., 1992. Geographic knowledge production through
GIS: towards a model for quality monitoring.
http://www.ncgia.ucsb.edu/Publications/Tech Reports/92/92-
12.PDF (accessed 26" April 2004).
Ehlschlaeger, C. R., Shortridge, A. M., and Goodchild, M. F.,
1997. Visualizing spatial data uncertainty using animation.
Computers & Geosciences, 23 (4), pp.387-395.
430
Foody, G. M., Atkinson, P. M., 2002. Current status of
uncertainty issues in remote sensing and GIS. In: Foody, G. M,,
Atkinson, P. M., (Eds.) Uncertainty in Remote Sensing and GIS.
Chichester, Wiley.
Gigerenzer, G., 2002. Reckoning With Risk: Learning to Live
with Uncertainty. London, Allen Lane.
Goodchild, M. F., 1991. Issues of quality and uncertainty. In
Muller, J. C., (Ed.) Advances in Cartography. New York,
Elsevier.
Hunter, G. J., 1991. New toold for handling spatial data quality:
moving from academic concepts to practical reality. Presented
at URISA '99, Chicago, USA.
Hunter, G. J., and Goodchild, M. F., 1996. Communicating
uncertainty in spatial databases. Transactions in GIS, | (1), pp.
13-25.
Jasc Software, 2004. PaintShop Pro. http://www.jasc.com
(accessed 26^ April 2004).
Jude, S., Jones, A.P., Andrews, J.E. and Bateman, L.J., 2002.
Visualising Future Coastal Landscapes. Proceedings of the GIS
Research UK 10th Annual Conference - GISRUK 2002.
University of Sheffield, UK. pp.141-144.
Krygier, J., 1994. Sound and Cartographic Visualization. In:
Taylor, D, and MacEachren, A., (Eds.) Visualization in Modern
Cartography. Oxford, Pergamon.
Lovett, A., Dockerty, T., Appleton, K., Sünnenberg, G., 2003.
GIS-based visualisation of potential climate change impacts on
rural landscapes. Presented at Geocomputation 2003, University
of Southampton, UK.
Terrex, 2004. TerraVista. http://www.terrex.com (accessed 26^
April 2004).
Warren-Kretzschmar, B., van Haaren, C., 2004. Online
Landscape Planning — What does it take? A case study in
Kónigslutter am Elm. Presented at Online Landscape
Architecture: The 5th [International Conference on Information
Technologies in Landscape Architecture, Anhalt University of
Applied Science, Dessau, Germany.
Willows, R. I., Connell, R. K., (Eds.) 2003. Climate adaptation:
risk, uncertainty and decision-making. UKC/P Technical
Report. Oxford, UKCIP
YT
KEY V
ABSTE
This pa
softwar
modele
the hig]
vertical
Besikta
model «
Develo
tools,
applica
Further
daily li
CAD,
photogi
measur
been d
maps,
improv
3D vir
admini:
and cor
While
investis
applica
in 90s.
virtual
make n
The 3T
can be
In addi
models
interne
Nowad
approat
existing
manual
Photog
about
like(Gr
process
visuali;
3D ci
inform:
provide