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Multispectral and Hyperspectral Remote Sensing of Quaternary Sediments in Tule and Snake Valleys, Lake Bonneville, Utah

Hassani, Kianoosh
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1503417442819968

Abstract Details

2017, Master of Science (MS), Ohio University, Geography (Arts and Sciences).
Lake Bonneville was the largest water body that accumulated in the Great Basin during the late Pleistocene. Its latest major lacustral cycle lasted from 30 ka to 12 ka and much evidence of the lake remains are still evident in the landscape today. This thesis investigates the use of Landsat-8 multispectral imagery for mapping the Quaternary deposits in the Tule Valley portion, and Hyperion (EO-1) hyperspectral data for mapping part of the adjacent Snake Valley of Lake Bonneville. Maximum likelihood classification was applied for Landsat 8 data, and the two spectral analysis approaches of linear spectral unmixing and spectral angle mapper (SAM) were applied to the Hyperion dataset. Furthermore, X-ray diffraction (XRD) analysis of a Lake Bonneville marl sediment sample characterized the dominant minerals in that sample. This investigation relied on Sack's (1990) Quaternary geologic map of Tule Valley as the reference for the remote sensing analysis. This study investigates if those sources of information can approach in quality and detail the traditional map that relies on fieldwork and air photo interpretation. Results illustrate that hyperspectral and multispectral data have potential value for Quaternary geological mapping. Maximum likelihood classification yielded overall accuracy of 51% with successful discrimination of Qlf, Qeg, Qes, Qlm, Qac, and bedrock. However, complete separation between several lacustrine and alluvial classes was not achieved. In general, the Hyperion spectral angle mapper (SAM) and spectral unmixing results discriminated relatively well among the three endmembers of calcite, gypsum, and quartz across portions of the Snake Valley study area. The high fraction abundance values on the fractional images reliably represented pixels dominated by calcite, gypsum, or quartz. Some confusion between classifications are attributeded to the local mixing of classes at the pixel scale, overlap in mineralogy, similarities in the nature of surface weathering, and the limited spectral resolution of the Landsat image. Results indicate that these methods have value for mapping extensive areas of Lake Bonneville and other desert lake basins faster and more efficiently than has previously been possible.
Dorothy Sack (Advisor)
Edna Wangui (Committee Member)
Timothy Anderson (Committee Member)
106 p.
Geographic Information Science; Geological; Physical Geography; Remote Sensing
multispectral remote sensing; hyperspectral remote sensing; Quaternary sediments; geological mapping; Lake Bonneville; Tule Valley; Snake Valley; Paleolake

Recommended Citations

Citations

  • Hassani, K. (2017). Multispectral and Hyperspectral Remote Sensing of Quaternary Sediments in Tule and Snake Valleys, Lake Bonneville, Utah [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1503417442819968

    APA Style (7th edition)

  • Hassani, Kianoosh. Multispectral and Hyperspectral Remote Sensing of Quaternary Sediments in Tule and Snake Valleys, Lake Bonneville, Utah. 2017. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1503417442819968.

    MLA Style (8th edition)

  • Hassani, Kianoosh. "Multispectral and Hyperspectral Remote Sensing of Quaternary Sediments in Tule and Snake Valleys, Lake Bonneville, Utah." Master's thesis, Ohio University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1503417442819968

    Chicago Manual of Style (17th edition)

ohiou1503417442819968
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This open access ETD is published by Ohio University and OhioLINK.