<p> This thesis provides a review of the development of hydrographic survey equipment and supporting geospatial equipment and technology such as GPS. Using SonarWiz, a sonar image processing software package, lakebed classification methodologies were evaluated for mapping Buffalo Reef in Lake Superior located near Gay, Michigan. The goal was to develop an approach to mapping the reef bed and delineating various components of the lake bottom, including stamp sands, which are migrating from the abandoned Gay copper processing stamp mill to the reef. This contamination of the reef is having an adverse effect on habitats important to local flora and fauna. </p><p> Sonar data was collected with an Edgetech 4125 side-scan sonar and an Iver3, a fully autonomous under water vehicle sonar, which has bathymetry and side-scan capabilities. Both systems are owned and operated by the Great Lake Research Center at Michigan Technological University. </p><p> Sonar image post-processing was complete utilizing SonarWiz 7, ArcGIS 10.5 and ERDAS Imagine. The resulting classification is composed of 6 information classes: cobble, cobble/stamp sand with different level intensity returns (low, medium, and high), trend of stamp sand, sandy waves and shadow which indicates mostly rock/ bedrock. The cobble/stamp sand had two distinct spectral classes: high intensity returns and low intensity returns for Iver 3, three distinct spectral classes: high intensity returns, medium intensity returns and low intensity returns for Edgetech 4125. The Edgetech 4125 classification excluded shadow area automatically. </p><p> The final step was an interpretation of lakebed features based on ground truth samples and photographic images from the bottom surface. Recommendations for future research are presented.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10683388 |
| Date | 14 March 2018 |
| Creators | Kulunk, Hasan Salih |
| Publisher | Michigan Technological University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
Page generated in 0.0022 seconds