Application of hyperspectral remote sensing in detecting and mapping Sericea lespedeza in Missouri

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Application of hyperspectral remote sensing in detecting and mapping Sericea lespedeza in Missouri

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/5051

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dc.contributor.advisor Wang, Cuizhen en
dc.contributor.author Zhou, Bo en_US
dc.coverage.spatial Missouri -- Mark Twain National Forest
dc.date.accessioned 2010-01-12T19:09:05Z
dc.date.available 2010-01-12T19:09:05Z
dc.date.issued 2007 en_US
dc.date.submitted 2007 Spring en
dc.identifier.other ZhouB-050407-T6737 en_US
dc.identifier.uri http://hdl.handle.net/10355/5051
dc.description The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. en_US
dc.description Title from title screen of research.pdf file (viewed on November 9, 2007) en_US
dc.description Includes bibliographical references. en_US
dc.description Thesis (M.A.) University of Missouri-Columbia 2007. en_US
dc.description Dissertations, Academic -- University of Missouri--Columbia -- Geography. en_US
dc.description.abstract When conservationists in Missouri realized that sericea lespedeza was taking its toll by threatening the healthy growth of economic vegetation, they decided to start controlling the invasion of this species. A major challenge encountered is to map the extent of its spatial spread. While satellite remote sensing and aerial photography have been available for many years, newer detection technologies such as hyperspectral sensors have made it possible to acquire large-scale laboratory-like spectra of sericea patches and surrounding natural grasses in the air. In this study, sericea was mapped using the Airborne Imaging Spectrometer for Application (AISA) sensor that records images at high spectral (9nm bandwidth, visible-infrared) and spatial (1̃m) resolution. Ground spectra were measured using the FieldSpecPro Full Range (FR) spectroradiometer from Analytical Spectral Devices (ASD, 2006). The study area is a grass field within the Mark Twain National Forest. The AISA images were processed with three different classification methods, and the results are validated based on field surveys. Major findings include: (1) the averaged sericea spectra is more accurate for mapping purposes; (2) moderate spectral response instead of strong spectral response is better in sericea mapping for they have less confusion with other classes; and (3) the MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) approach is the best for mapping sericea. en_US
dc.language.iso en_US en_US
dc.publisher University of Missouri--Columbia en_US
dc.relation.ispartof 2007 Freely available theses (MU) en_US
dc.subject hyperspectral remote sensing. en_US
dc.subject hyperspectral remote sensing en_US
dc.subject.lcsh Lespedeza cuneata -- Control en_US
dc.subject.lcsh Lespedeza cuneata -- Remote sensing en_US
dc.title Application of hyperspectral remote sensing in detecting and mapping Sericea lespedeza in Missouri en_US
dc.type Thesis en_US
thesis.degree.discipline Geography en_US
thesis.degree.grantor University of Missouri--Columbia en_US
thesis.degree.name M.A. en_US
thesis.degree.level Masters en_US
dc.identifier.merlin .b61277253 en_US
dc.identifier.oclc 180990540 en_US
dc.relation.ispartofcommunity University of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2007 Theses


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