to be generated to avoid an insufficient terrain 
description caused by the interpolation algorithm of the 
final DTM. For that purpose the boundaries of these 
areas must be located. Then the planar triangles from 
the preliminary TIN forming these areas afford a 
sufficient surface description to interpolate the artificial 
points. 
5.5 Data update and follow-up products 
Within the GIS Interface of HIFI subroutines for data 
editing are available. In addition to the update of data 
the TIN us updated in real time. Thus after each data 
modification step as explained above an updated TIN is 
present and the modification actions can be checked at 
any time deriving DTM follow-up products, e.g. con- 
tours or shaded relief representations. Also the quality 
test is always available to check the improvements of the 
terrain description. 
5.6 Point distribution 
The final DTM generation with the finite element 
method realized in the program HIFI needs two main 
parameters a priori: 
- the mesh width of the resulting grid for the interpo- 
lated points and 
- the interpolation weight for the primary data. 
Up to now not enough attention is paid to the deter- 
mination of these parameters. Usually they are chosen 
empirically or due to the conditions of a project without 
knowing wether the parameters meet the requirements 
or not. Therefore the quality of a created DTM could be 
overestimated by the user or the potential of the primary 
data is not used fully for the DTM generation. 
In the following a method for a realistic estimation of the 
mesh width is described. The lowest hierarchic level of 
the data organization in the HIFI data base is called a 
subarea, which includes 8*8 meshes. Within every 
subarea there should exist a minimum of primary data. 
This minimum is the only a priori value for the following 
calculations. 
In a first step a mesh width is automatically proposed, 
which is derived from the ratio of the whole DTM area 
and the primary data within this area. This mesh width 
can be changed optionally by the user. Using this mesh 
width a test of the homogeneity of the point distribution 
can be started. For that all data must be organized by 
subareas and the subareas by point classes (e.g. class i : 
n to m points). The result is represented and can be 
analyzed by an image with colour coded subareas or in 
a summary way by a histogram (figure 4). 
- 
o 
S 9 
u 8 
b 7 
a 6 
r 5 
e 4 
3 
a 
2 
S 
1 
0 
  
point class 
Figure 4: Histogram of a point distribution 
If a great inhomogeneity within the point distribution is 
detected artificial points optionally are interpolated by 
means of the TIN within areas of sparse or none 
reference point coverage to support the interpolation 
algorithm for the final DTM. 
6. EXAMPLES AND EXPERIENCES 
The approach has been tested by two practical examples. 
As a first data set digitized contours were preprocessed. 
The extension of the project area is about 3*3 km and 
HSE 
= 
Figure 5: Detected gross errors along a piece of a 
contour line