2006 Philadelphia Annual Meeting (22–25 October 2006)

Paper No. 9
Presentation Time: 10:15 AM

USING GIS TECHNOLOGY FOR FABRIC ANALYSES IN STRUCTURAL GEOLOGY


BHATTACHARYYA, Prajukti, Geography and Geology, University of Wisconsin - Whitewater, 120 Upham Hall, 800 Main Street, Whitewater, WI 53190 and CZECK, Dyanna, Geosciences, Univ of Wisconsin - Milwaukee, PO Box 413, Milwaukee, WI 53201, bhattacj@uww.edu

Fabric analysis is an important part of structural studies and can be used to determine deformation history in regional-scale shear zones and tectonites. Fabric analysis is most powerful when a variety of fabric elements including foliations, lineations, small-scale shear zones, and shear bands are considered simultaneously. Here, we present an approach to fabric analyses using GIS techniques. For this study, we selected one orthogneiss outcrop within the Mountain Shear Zone in Oconto County, WI.

The orthogneiss contains several generations of cross-cutting fabrics defined by alignment of biotite and hornblende. The fabrics exposed at this outcrop include a pervasive, subvertical foliation locally reoriented by centimeter scale anastomosing shear zones with varying orientations and discrete, millimeter scale shear zones. Other fabric elements include mafic enclaves and veins. Unfortunately, on much of the outcrop, these fabrics and structural elements are indistinguishable due to weathering or lichen cover.

With the use of tape and compass, we constructed a local reference frame of 6 meters by 6 meters and recorded GPS coordinates for the corner points using a Trimble TSC1 datalogger and Asset Surveyor software with submetric accuracy. Where visible, we color coded and traced fabric elements onto transparent plastic sheets, which were oriented with respect to the local reference frame. We digitized the tracings into GIS by means of a digitizing tablet and digital photographs and created GIS layers for each group of fabric elements. Using the Spatial Analysis tools included in the ESRI ArcGIS 9 package, we characterized attributes including circular variance, sinuosity, and connectivity of the different fabrics. We also determined likely orientations of fabrics in the areas where they are not exposed.

Our study shows promise for the use of GIS in future structural fabric studies. The spatial statistical tools in GIS allow us to further our understanding of fabric evolution and the linkages between fabric elements. It is possible to create detailed maps of various structural features, use standard data modeling to interpolate data in unexposed areas, and statistically determine spatial correlations between various structural features.