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Spatial Mapping of Strain Patterns Using GIS

Miller, Roy H, III
http://orcid.org/0000-0002-3467-2847
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1441362674

Abstract Details

2015, Master of Science (MS), Bowling Green State University, Geology.
Although there have been advances in finite strain analysis like the Rf/f and Fry methods, there are still assumptions, such as strain homogeneity throughout the sample, that limit the amount of information that can be derived from these methods. As many naturally deformed rocks have heterogeneous strain distributions, which can reveal important information about process and/or history, it is desirable to be able to efficiently analyze heterogeneous strain. This study uses semivariograms in a GIS environment to recognize and characterize heterogeneous strain. By using a series of synthetic datasets, selected to mimic various types of natural deformation, an understanding of the patterns is developed that is then applied to a naturally deformed sample of ooids, which displays obvious spatial variations in strain. The results of the semivariogram analysis are then compared to a conventional strain analysis using Fry plots. Omnidirectional semivariograms for the synthetic models have ranges from 0.52 to 5.84 mm) for long axis orientation and 0.99 to 6.56 mm for the strain ratio. Directional semivariograms show evidence of anisotropy for most models for both long axis orientation and strain ratio. Conventional strain analysis like descriptive (or shape) statistics and the Fry method summarized long axis orientation and strain ratio, but they do not account for strain heterogeneity or spatial variance. Omnidirectional and directional semivariograms demonstrated evidence for strain heterogeneity and anisotropy but do not account for magnitude or nature of heterogeneity nor do they summarize general long axis orientation and strain ratio. Analysis of the natural ooid sample using omnidirectional semivariograms demonstrated strain heterogeneity as well as anisotropy with directional semivariograms. Fry plots show N-NNW directional preference for some of the subsets but had uninterpretable plots with other subsets. It can be concluded that while semivariograms account for strain heterogeneity, they do not characterize nature or magnitude nor do they summarize long axis orientation and strain ratio. Semivariograms are not effective tools for finite strain analysis.
John Farver (Advisor)
Charles Onasch (Committee Member)
Peter Gorsevski (Committee Member)
99 p.
Geographic Information Science; Geology
Finite strain analysis; Semivariogram; GIS; Strain

Recommended Citations

Citations

  • Miller, III, R. H. (2015). Spatial Mapping of Strain Patterns Using GIS [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1441362674

    APA Style (7th edition)

  • Miller, III, Roy. Spatial Mapping of Strain Patterns Using GIS. 2015. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1441362674.

    MLA Style (8th edition)

  • Miller, III, Roy. "Spatial Mapping of Strain Patterns Using GIS." Master's thesis, Bowling Green State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1441362674

    Chicago Manual of Style (17th edition)

bgsu1441362674
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© 2015, all rights reserved.
This open access ETD is published by Bowling Green State University and OhioLINK.