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uu M 
Sofar existing satellite systems, in particular Landsat, are capable to 
provide primarely information on the areal extent of the snowcover. In this 
respect we have to keep always in mind, that what we receive by a sensor 
system is the spectral response - be it reflection or emission - from a 
two-dimensional surface. But what we want to know, are the identity and the 
conditions of a three-dimensional object. To obtain this information proper 
interpretation methods have to be developed and applied. 
With the launch of Landsat-3 and HCMM it will be possible to get better data 
on the surface temperature and in particular on its moisture condition. For 
efficient monitoring data on the snowdepth or - even better - on the water 
equivalent would be essential. There was great hope that these data may be 
obtained from MW-devices. Numerous experiments were carried out in this 
direction (MOORE, 1974) but up to now no definite solution could be presented. 
Leading experts in this field doubt that a truely three-dimensional measure- 
ment of the snowpack will be possible by remote sensing techniques under all 
conditions. 
y Survey On existing methods 
To achieve the previously mentioned goals, quite a many different methods 
exist and for a proper selection the following points have to be considered 
in particular: 
- objective(s) 
- extent of study area (mapping scale) 
- accuracy needed 
- time available to produce the results 
- financial and manpower resources 
- equipment available 
Analog methods, which include everything from simple photointerpretation 
to complex optical and/or electronical devices, are still very often more 
suitable and economical, especially when only the mapping of the areal extent 
of the snowcover is required. Photointerpretation does not ask for expensive 
technical equipment and is by far the best beginning to the analysis of re- 
motely sensed data. 
Only for longterm operational snowmapping, where the data processing should 
be automated and speeded up as much as possible, machine-aided methods are 
recommended. They allow an objective comparison over large areas. But the 
initial investments to set up the necessary software for preprocessing, 
feature extraction and output of results are very substantial. Today 
digital classification methods are dominating, but analog or 
hybrid systems are considered, too.