International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004
3.2 Visualizing the moose density in the third dimension
Much of cartography's familiarity with three-dimensional
landscapes originates from digital elevation models (DEMs),
panoramas, sculpted physical models and orthographic globes.
The fundamentals to design "classic" three-dimensional
visualisations, using greyscale DEMs, vertical exaggeration and
illumination are explained by Raper (Raper, 1989) and
Petterson (Patterson, 1999) among others.
The possibilities to use the third dimension to visualize thematic
data have been explored by Krisp & Fronzek among others. The
use of the third dimension can aid the visualisation of spatial
datasets consisting of two thematic variables and allows
comparing them more directly. It can also help to stress certain
components of the information. Selecting and intensifying of
specific parts of the information is especially important in the
creation of thematic maps (Krisp & Fronzek, 2003).
Figure 5 illustrates the moose density in the third dimension.
Hills indicate a high moose density while valleys a low amount
of moose. The map stresses this information further by a color
scale from red (high) to green (low).
Moose density and moose traffic accident locations in
Uusimaa, Finland for January, February, March 2002
FHalumbl University of Technology. Cirie graphy 8 Oasinl'ecessibes II
PES
Figure 5. Moose density in winter 2002 for Uusimaa, Finland in
a three-dimensional map with a color scale from red to green
3.3 Integrating moose accident data
We include accident data considering passenger vehicles and
moose from the year 2002. The accident data has been collected
over the whole year. We classified the seasons into different
parts, taking into consideration the moose migration patterns
shown in Table 1.
Time Habitat Movement
Winter winter pasture Little
(January to
March)
Spring (April — Fast and straight
May)
Summer (June Unspecific, abundant
to August)
summer pasture
Early Autumn
(September-
October)
autumn pasture Mating season
Late Autumn
(November-
December)
Slow and delay
Table 1. Moose movement patterns in different seasons
To visualize and analyze changes in the accident patterns of the
year we integrated the different maps into an animation by
using the Macromedia Director authoring tool. Figure 6
illustrates the system as a screenshot for the winter season 2002.
Moose accidents 2002, Uusimaa, Finland
Sesson ‘Activity
>
Verger. Januery te Maran
€ Mete accident
482888500000
HedspMbà Vesteersity MCTe t hielo gy. Carteqeaphy A Geeintere Toi
Figure 6. Moose density and accidents in the Winter 2002,
Uusimaa, Finland
The system shows changes in the accident data over one year.
Connecting this information with the moose density
Figure 7 illustrates the moose density by using the third
dimension.
in a : E A
Figure 7. Moose density overlay with the road network and
moose accidents 2002, Kirkkonummi region, Finland
In the Kirkkonummi area west of Helsinki, we can identify a
road cutting through two major moose habitats. The road is not
fended (at the time of the data collection) and shows a number
of moose accidents in this area.
3.4 Four dimensional animation
A four-dimensional map integrates the x, y locations as well as
a z variable over time (t) To create a four-dimensional
animation we generate three-dimensional maps for all available
years (2001-2003) and combine them into an interactive system
illustrated in Figure 8. The system has been put together by
using the Macromedia authoring tool.
412
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