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Proceedings Paper

Hyperspectral image unmixing over benthic habitats
Author(s): Miguel Vélez-Reyes; Samuel Rosario-Torres; James A. Goodman; Enid M. Alvira; Alexey Castrodad
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Paper Abstract

Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Hyperspectral remote sensing has great potential to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. However, utilizing hyperspectral unmixing to map these areas requires compensating for variable bathymetry and water optical properties. In this paper, we compare two methods to unmix hyperspectral imagery in estuarine and nearshore benthic habitats. The first method is a two-stage method where bathymetry and optical properties are first estimated using Lee's inversion model and linear unmixing is then performed using variable endmembers derived from propagating bottom spectral signatures to the surface using the estimated bathymetry and optical properties. In the second approach, a nonlinear optimization approach is used to simulatenously retrieve abundances, optical properties, and bathymetry. Preliminary results are presented using AVIRIS data from Kaneohe Bay, Hawaii. SHOALS data from the area is used to evaluate the accuracy of the retrieved bathymetry and comparisons between abundance estimates for sand, algae and coral are performed. These results show the potential of the nonlinear approach to provide better estimates of bottom coverage but at a significantly higher computational price. The experimental work also points to the need for a well characterized site to use for unmixing algorithms testing and validation.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650U (7 May 2007); doi: 10.1117/12.721049
Show Author Affiliations
Miguel Vélez-Reyes, Univ. of Puerto Rico at Mayagüez (United States)
Samuel Rosario-Torres, Univ. of Puerto Rico at Mayagüez (United States)
James A. Goodman, Univ. of Puerto Rico at Mayagüez (United States)
Enid M. Alvira, Univ. of Puerto Rico at Mayagüez (United States)
Alexey Castrodad, Univ. of Puerto Rico at Mayagüez (United States)


Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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