The running-cone method is a straightforward means of analysing the geometry of conical folds over a range of scales from outcrop to regional map. The method is based on a 3-D directional averaging process in which strike-and-dip data from natural folds may be utilized to constrain the conical geometry of regional fold sets. The orientations of local cone axes are obtained from a sequence of measurements of poles to bedding using triplets of adjacent data. The repetition of the procedure using the axes orientations yields the orientations of the poles to a surface smoother than that of the original bedding. The final steps of any single data sequence analysis, deemed significant when showing permanent orientation distributions, may highlight conical fold geometries not readily apparent from the cumulative data set. The introduction of a threshold to remove adjacent data with subparallel orientations speeds the convergence of the analysis to a unique solution. The method is tested using natural conical folds in the Dolomites, northern Italy, producing three preferred fold axes plunging to the NE, SE and WSW. These orientations are consistent with the regional fold trends.
The running-cone method for the interpretation of conical fold geometries: An example from the Badia Valley, Northern Dolomites (NE Italy)
Rossi G.
2005-01-01
Abstract
The running-cone method is a straightforward means of analysing the geometry of conical folds over a range of scales from outcrop to regional map. The method is based on a 3-D directional averaging process in which strike-and-dip data from natural folds may be utilized to constrain the conical geometry of regional fold sets. The orientations of local cone axes are obtained from a sequence of measurements of poles to bedding using triplets of adjacent data. The repetition of the procedure using the axes orientations yields the orientations of the poles to a surface smoother than that of the original bedding. The final steps of any single data sequence analysis, deemed significant when showing permanent orientation distributions, may highlight conical fold geometries not readily apparent from the cumulative data set. The introduction of a threshold to remove adjacent data with subparallel orientations speeds the convergence of the analysis to a unique solution. The method is tested using natural conical folds in the Dolomites, northern Italy, producing three preferred fold axes plunging to the NE, SE and WSW. These orientations are consistent with the regional fold trends.File | Dimensione | Formato | |
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