The Generation of a Mass Point Model from Surface Gravity Data.
OHIO STATE UNIV COLUMBUS DEPT OF GEODETIC SCIENCE AND SURVEYING
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The generation of a point mass model from surface gravity data requires the employment of sophisticated techniques mainly because a large number of unknowns has to be determined from large number of data. The method proposed relies on the transformation of the problem into the frequency domain. The calculation of the coefficients of the transformation matrix requires the evaluation of an integral of an isotropic kernel with respect to a limited area on the unit sphere, if mean values are used as data. An optimal algorithm for the approximate calculation in the sense of Sard, using Peanos theorem for functions on a sphere, is presented. The relation between the depth of a point mass layer and the mean value block size is derived by comparing the spectrum of the two operators.