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Remote sensing of tidal freshwater marsh elevation, channels, and vegetation structure

dc.contributor.advisorEngelhardt, Katharinaen_US
dc.contributor.authorElmore, Annette Hallen_US
dc.date.accessioned2008-06-20T05:32:01Z
dc.date.available2008-06-20T05:32:01Z
dc.date.issued2008-03-19en_US
dc.identifier.urihttp://hdl.handle.net/1903/8053
dc.description.abstractI mapped three elevation classes in a Mid-Atlantic tidal freshwater marsh using QuickBird multi-spectral imagery and field measurements of elevation and channel networks. The elevation map reveals heterogeneous surfaces at a 2.4 m pixel scale. Field collected vegetation cover data differed among the three elevation classes. Species richness and the number of positive associations among species were higher in the mid- and high-marsh than the low marsh. The number of negative associations among species increased with rising elevation. Random forest classification of elevation class using species cover vectors selected only <em>Impatiens capensis</em> and <em>Nuphar luteum</em> and had an out of box predictive error of 26%. My research shows that the vegetation of freshwater tidal marshes is diverse with ill-defined boundaries between distinct communities. Yet vegetation shifts beyond the traditional low and high marsh communities could be detected, which should provide a useful tool for restoration and management.en_US
dc.format.extent4969231 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleRemote sensing of tidal freshwater marsh elevation, channels, and vegetation structureen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentBiologyen_US
dc.subject.pqcontrolledEnvironmental Sciencesen_US
dc.subject.pqcontrolledBiology, Ecologyen_US
dc.subject.pqcontrolledRemote Sensingen_US
dc.subject.pquncontrolledwetlandsen_US
dc.subject.pquncontrolledemergent macrophytesen_US
dc.subject.pquncontrolledenvironmental gradienten_US
dc.subject.pquncontrolledQuickBirden_US


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