The kriging variogram’s dependent predictiv in Figure 2. In general, the lower the e
location, the better is the prediction of the sp The final spatial model permits us to visual
volumes as well as cuts in any plane of the
Figure 3. Geospatial representation of Up approximately the upper 500 m of the
constituted of UHW and voxels containing black dots. Vertical exaggeration in fig
4. DISCUSSION AND CONCL
This research has explored the potential modelling tools for the study of marine pel
review of common GIS indicates that these mostly
lack the
necessary functions
representation of gradual phenomena, primo study of marine ecosystems. However
geomodelling tools for representation of t promising, which is illustrated in this paper
3D solution to visualization of a water mass Beaufort Sea, constructed with Paradigm
Integration of volumetric representation in a an important advance towards an optimal ma
must also include representation and analys static vertical cuts. On the contrary, geomo
be adapted to the marine environment b functions for oceanographic research such
and analyses. However, all spatial modelling the pelagic environment would also bene
spatial data structure that takes into conside nature and fuzzy boundaries of the pelagic en
ctive error is presented error for a specific
spatial model. alize iso-surfaces and
he water mass Figure 3 and enables spatial 3D analyses
and intersection. This case study s volumetric representation develope
tools can be used to extend usual i pelagic phenomena from 2D st
environment.
pper Halocline Water on the Mackenzie shelf in summer 2009 e water mass contained within the spatial model. Scale indicat
ing more than 60 of UHW are coloured-filled. Visible samp figure is 75 times that of reality. Spatial model was constructed
CLUSIONS
ial of 3D geospatial pelagic ecosystems. A
ese software products ns
for volumetric
mordial for geospatial ver, performance of
f this environment is er by a snap-shot of a
ss in the south-eastern m Gocad Figure 3.
a GIS environment is marine GIS. This tool
lyses functions of 2D modelling tools could
by improving basic ch as image treatment
ing tools conceived for enefit from including
ideration the dynamic environment.
Our future research will explor geospatial modelling tools for the
ground data in the identification organic carbon fluxes in the Beaufo
5. ACKNOWLED
