Using hyperspectral data to classify vegetation at the plant functional type-level in mountain terrain at three spatial resolutions

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Publication Type thesis
School or College College of Social & Behavioral Science
Department Geography
Author Schaaf, Abigail N
Title Using hyperspectral data to classify vegetation at the plant functional type-level in mountain terrain at three spatial resolutions
Date 2010
Description Hyperspectral data covering the visible, near infrared, and shortwave infrared portions of the electromagnetic spectrum have been used to map vegetation at the plant functional type and species levels in a variety of ecosystems. Vegetation maps are basic to the study and analysis of natural resources and are an important component in documenting and understanding the impacts of environmental changes in ecosystems due to human-induced changes (e.g., climate change). Multiple methods for mapping vegetation have been developed to take advantage of the large number of bands (> 200) and spectral contiguity that hyperspectral data provide. The purpose of this study is to determine what the limitations and potential areas of success are for using hyperspectral remote sensing data to classify vegetation cover in steep mountainous terrain at the plant functional type level.
Type Text
Publisher University of Utah
Subject Hyperspectral; Mountain terrain; Plant functional type; Spatial resolution; Spectral mixture analysis; Vegetation classification
Subject LCSH Vegetation mapping
Dissertation Institution University of Utah
Dissertation Name MS
Language eng
Rights Management ©Abigail N. Schaaf
Format Medium application/pdf
Format Extent 629,198 bytes
Source Original in Marriott Library Special Collections, QK3.5 2010 .S34
ARK ark:/87278/s6w6717v
Setname ir_etd
Date Created 2012-04-23
Date Modified 2018-03-15
ID 192287
Reference URL https://collections.lib.utah.edu/ark:/87278/s6w6717v
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