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The AAPG/Datapages Combined Publications Database

Utah Geological Association

Abstract


Proceedings of the First International Conference on the New Basement Tectonics, 1974
Pages 423-436

Spatial Analysis of Basement and Cover Linears by Optical Previous HitDiffractionNext Hit - Methods, Results, and Interpretation

Howard J. Pincus, Thomas W. Doe

Abstract

We are analyzing basement and cover lineaments using Abbé’s pioneering work in optics (1873). The basic technique consists of spectral analysis of the input’s spatial information content by optical Previous HitdiffractionNext Hit. The input is a reduced transparent reproduction of the photograph or map being studied. This transparency functions as a Previous HitdiffractionNext Hit grating with unknown spatial properties. The resulting Previous HitdiffractionNext Hit pattern is the two-dimensional Fourier amplitude transform of the input image. This transform is a graph of the distribution of orientations and spatial frequencies of the elements in the input. With additional optics, a filtered, reconstructed input image can be formed by blocking out selected light rays in the transform plane. Filtering can suppress dominant alignments so that obscure features are more easily studied, and can aid in analyzing complicated distributions by systematically removing selected components of the input. Through their Previous HitdiffractionNext Hit patterns, fabrics can be described, regardless of scale, in terms of spacings, directions, elongations, and symmetries. Contrasts in fabric can be characterized through contrasts in transforms.

We have processed ERTS photography Previous HitfromNext Hit the U.S.A. and Canada. Apparent dihedral angles are detectable in the transforms. Fourier transform processing integrates the contribution of linears independent of relative locations in the inputs. Degree of preferred orientation and concentration of spatial frequency can be evaluated quantitatively. Filtering may assist in examining relatively obscure linears.

Relations between spatial frequency and direction might be important. Variability or dispersion in the data should not necessarily be dismissed as “noise”, for this might be of genetic significance.


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