An evaluation of three techniques for the prediction of gravity anomalies in Canada
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Abstract
Recent studies have shown that the Canadian height control network, which was defined on the basis of normal gravity, suffers from the influence of gravity anomalies that can introduce significant systematic regional distortions. Proposals have been made for a new definition of heights for Canada which would be based on observed gravity values. Since, observed gravity is not now available at all points along levelling paths, (as required by the new definition), techniques suitable for the prediction of point gravity values at bench marks, say, are, therefore, required.
The performances of three prediction techniques – least-squares surface fit, least-squares collocation, and weighted mean methods – in three terrain situations in Canada were evaluated. The terrain situations considered correspond to the flat, gently rolling, and mountainous terrain types. Test points were selected randomly from each terrain type considered, and the nine samples generated by using each technique to predict for point gravity anomalies at the selected points were vigorously tested statistically. The method of weighted means performed well in the three different types of terrain. It was the fastest of the three techniques, and the most economical in terms of computer time. The other two techniques gave good results in the flat, and rolling terrains, but did not perform so well in the mountainous terrain.