Abstract:
The basic activities of surveying and geodesy are acquiring data from field
observations. However, field activities are usually time consuming and
therefore expensive. Mathematical models are usually cheaply adapted to
densify more data required for a particular objective.
Such models should be formulated in a correct manner such that the predicted
quantities satisfy their required purpose.
In all cases, functions with specified properties must be used.
This study aims to:
1)
Obtaining empirical covariance functions that can be successfully
used in least squares prediction.
2)
Obtaining functions (polynomials) that can be used to develop a
practical surface.
Empirical covariance functions have been prepared from known and expected
data and have been tested in the interpolation.
The main conclusions of the study are as follows:
1)
Both models i.e. surface fitting and least squares prediction give
results of the same precision for flat areas.
2)
For areas up to 3x3 km2 contour plants of interval of 0.25m can be
produced provided six data points, evenly distributed.
