Exploiting nonlinear structure in hyperspectral coastal data

David Gillis; Jeffrey Bowles; Ellen Bennert; Daniel Korwan; Gia Lamela; Marcos Montes; William J. Rhea

doi:10.1117/12.680951

1 September 2006 Exploiting nonlinear structure in hyperspectral coastal data

David Gillis, Jeffrey Bowles, Ellen Bennert, Daniel Korwan, Gia Lamela, Marcos Montes, William J. Rhea

Proceedings Volume 6302, Imaging Spectrometry XI; 63020V (2006) https://doi.org/10.1117/12.680951
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

In this paper, we investigate the use of nonlinear structure to derive the physical characteristics of coastal data. In particular, we show how the physics of shallow water coastal regions lead to well defined nonlinear structures (manifolds) in the corresponding hyperspectral data. The exact form of this structure is determined by both the Inherent Optical Properties of the water column as well as the boundary conditions (bottom reflectance, depth). This structure is then used to develop efficient algorithms for searching large 'lookup tables' of precalculated spectra with known physical characteristics, which are used for estimating the various physical parameters (bathymetry, bottom type, etc.) of the scene. We assess our methods with data collected by the NRL PHILLS sensor at the Indian River Lagoon (IRL) in Florida. The IRL is a well-studied and characterized body of water that contains a number of different water and bottom types at various shallow (generally less than 8 meters, except in the shipping channel where depths can be as much as 18 m) depths. We show in particular that the search algorithm is able to produce valid results in a short amount of time, and compare our results with an IRL LIDAR bathymetry survey from early 2004.

Citation Download Citation

David Gillis, Jeffrey Bowles, Ellen Bennert, Daniel Korwan, Gia Lamela, Marcos Montes, and William J. Rhea "Exploiting nonlinear structure in hyperspectral coastal data", Proc. SPIE 6302, Imaging Spectrometry XI, 63020V (1 September 2006); https://doi.org/10.1117/12.680951

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