Southeastern Section - 67th Annual Meeting - 2018

Paper No. 11-17
Presentation Time: 8:00 AM-12:00 PM

EXPLORING THE POTENTIAL OF REMOTE SENSING AND GIS FOR GEOLOGICAL MAPPING OF WOODALL SHOALS, GA-SC


ADAIR, William A., BEITEL, Hayley R., HAMID, Zack A., HOSSAIN, Azad A.K.M. and MIES, Jonathan W., Department of Biology, Geology and Environmental Science, University of Tennessee at Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403

Remote sensing technology has been successfully used to map surficial geology for many years, especially in areas with little or no vegetation. An outcrop of various igneous and metamorphic lithologies at Woodall Shoals, GA-SC, provides an excellent opportunity to explore the potential of remote sensing technology for geologic mapping. The lack of vegetation at Woodall Shoals permits imagery to be easily obtained and for it to be analyzed using remote sensing and GIS technologies. Due to the small size of the study site, the wide variation of lithologies, and the scale of discrete structures and lithologic variation, high resolution data was needed to perform the analysis. A 30-cm- resolution visible and near infrared orthoimage of the study site was obtained from the USGS. In the field, very high-resolution imagery was obtained using a Nikon COOLPIX S9700 camera suspended vertically above the outcrop by a long pole. Individual images obtained in the field were stitched together and were georectified using the obtained USGS orthophoto for control.

A detailed field-based geologic map provided by Robert Hatcher was similarly georectified. This map was used for reference and as the source of training data for image classification. ERDAS Imagine and ArcGIS software were used to identify various lithologies using supervised classification algorithms. Two geologic maps were produced, one based on high-resolution field images and the other based on the USGS orthoimage.

Promising preliminary results inspire the expansion of this research using more detailed imagery with complete coverage acquired by unmanned aerial vehicles (UAVs) and hyperspectral image spectroscopy in the near future.