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        Spectral Unmixing Applied to Desert Soils for the Detection of Sub-Pixel Disturbances

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        Author
        (Howard), Jessica Stuart
        Date
        2012-09
        Advisor
        Kruse, Fred A.
        Second Reader
        Olsen, Richard C.
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        Abstract
        Desert areas cover approximately one-fifth of the Earth, making it important to understand how disturbance affects arid regions on a spectral level. Remote sensing technology can be used to detect and characterize surface disturbance both literally (visually) and non-literally (analytically). Non-literal approaches may even allow detection of anthropogenic-related surface disturbances that are not visible in individual images or color composites. This is achievable through identification of differences in spectral reflectance among like soil components, both chemical and biological. Previous research suggests that surface disturbances cause alteration of soil properties, making it feasible to detect variation in reflectance signatures. This research supports that assumption and has determined that disturbance-related changes do have unique spectral characteristics in hyperspectral imagery that are detectable, even at the sub-pixel level and using endmembers from geographically different yet geologically similar regions.
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        http://hdl.handle.net/10945/17379
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          Spectral variability constraints on multispectral and hyperspectral mapping performance 

          Kruse, Fred A.; Fairbarn, K.G. (SPIE, 2013);
          Common approaches to multispectral imagery (MSI) and hyperspectral imagery (HSI) data analysis often utilize key image endmember spectra as proxies for ground measurements to classify imagery based on their spectral ...
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          Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement 

          Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R. (SPIE, 2013);
          Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were ...
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          Improving Identification of Area Targets by Integrated Analysis of Hyperspectral Data and Extracted Texture Features 

          Bangs, Corey F. (Monterey, California. Naval Postgraduate School, 2012-09);
          Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture features on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used ...
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