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Potential Species Distribution of Balsam Fir Based on the Integration of Biophysical Variables Derived with Remote Sensing and Process-Based Methods
Remote Sens. 2009, 1(3), 408-417; doi:10.3390/rs1030408
Communication

Evaluating Principal Components Analysis for Identifying Optimal Bands Using Wetland Hyperspectral Measurements From the Great Lakes, USA

1,*  and 2
Received: 13 May 2009; in revised form: 12 August 2009 / Accepted: 12 August 2009 / Published: 18 August 2009
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Abstract: Mapping species composition is a focus of the wetland science community as this information will substantially enhance assessment and monitoring abilities. Hyperspectral remote sensing has been utilized as a cost-efficient approach. While hyperspectral instruments can record hundreds of contiguous narrow bands, much of the data are redundant and/or provide no increase in utility for distinguishing objects. Knowledge of the optimal bands allows users to efficiently focus on bands that provide the most information and several data reduction tools are available. The objective of this Communication was to evaluate Principal Components Analysis (PCA) for identifying optimal bands to discriminate wetland plant species. In-situ hyperspectral reflectance measurements were obtained for thirty-five species in two diverse Great Lakes wetlands. PCA was executed on a suite of categories based on botanical plant/substrate characteristics and spectral configuration schemes. Results showed that the data dependency of PCA makes it a poor, stand alone tool for selecting optimal wavelengths. PCA does not allow diagnostic comparison across sites and wavelengths identified by PCA do not necessarily represent wavelengths that indicate biophysical attributes of interest. Further, narrow bands captured by hyperspectral sensors need to be substantially re-sampled and/or smoothed in order for PCA to identify useful information.
Keywords: hyperspectral; principal components analysis; wetlands; invasives; optimal bands; Great Lakes hyperspectral; principal components analysis; wetlands; invasives; optimal bands; Great Lakes
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Torbick, N.; Becker, B. Evaluating Principal Components Analysis for Identifying Optimal Bands Using Wetland Hyperspectral Measurements From the Great Lakes, USA. Remote Sens. 2009, 1, 408-417.

AMA Style

Torbick N, Becker B. Evaluating Principal Components Analysis for Identifying Optimal Bands Using Wetland Hyperspectral Measurements From the Great Lakes, USA. Remote Sensing. 2009; 1(3):408-417.

Chicago/Turabian Style

Torbick, Nathan; Becker, Brian. 2009. "Evaluating Principal Components Analysis for Identifying Optimal Bands Using Wetland Hyperspectral Measurements From the Great Lakes, USA." Remote Sens. 1, no. 3: 408-417.


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