(2) density of data: some cells could not be fitted to the
required accuracy of fit for lack of sufficient data. This
implies a need for differential density for different types
of terrain for a required accuracy of fit and fixed cell size
or a variable cell size for a fixed density of data.
(3) Percentage overlap in relation to terrain type and density
of data. This will have to be investigated further in order
to establish their relationships.
CONCLUSION
The method of least squares polynomial surface fitting with overlapping
data has been shown to be a working alternative in functional digital
elevation modelling. However the actual amount of data overlap in percent
is a function of many factors the main ones being terrain type, data
density and accuracy of fit. The author is still working on this to
establish these parameters and their relationships.
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Doyle, F.J., 1978
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