) REAL 
rawn from the 
primitives and 
J real terrain 
region (south 
by accidental 
morphologic 
veen 840 200 
and 176 880, 
d 243.000 m. 
4 points. Two 
jelimited from 
‘mation was 
system. This 
rm. 
Pts 
0.65 
  
0.71 
| Versus semi 
/ariants of opt 
the fidelity of 
2. information. 
curacy of the 
and overall 
pared to semi 
10% ). Finally, 
uding the X 
the rule base 
it also higher 
By including the Z information in the modelling process, 
the accuracy increases substantially. At the same time, the 
inclusion of X information results in a considerable gain in 
efficiency. From the results of the modelling experiments 
applied to ideal geometric primitives, a simulated composite 
surface and real terrain morphology, additional rule bases 
were set up. Rule base to systemize selective modelling 
and rules for the procedure of the subsequent phase of 
semi- automated modelling, in order to achieve a balance 
between X and [1 information, allow for optimum sampling. 
The above method allows promissing applications in 
descriptive geomorphology. Both morphographic and 
morphometric attributes of geoforms can be derived from a 
topographic map by visual interpretation or from a DTM by 
either visual or automated procedures. Morphometric 
attributes refer essentially to the geometry of the geoforms, 
including shape and profile of yhe topography, aspect, 
configuration and contour design of the forms, and drainage 
pattern. Morphometric attributes refer to the dimensions of 
the geoforms, including relative elevation, vally density and 
slope steepness. On-going research explores specifically 
the possibility of using the ideal geometric primitive surfaces 
for computer-assisted recognition of elementary landforms, 
as a basis for environment. 
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Charif, M.,1991, Echantillonnage optimal pour modele 
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Charif, M., Makarovic, B., 1988. Optimizing progressive and 
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Fredrikson, Poul., Jacobi, Ole., Kubik, K. 1983. Optimal 
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797