Using hyperspectral imaging to characterize the coastal environment

In shallow waters visible remote sensing systems frequently image the bottom including features, such as grass beds and coral reefs. Resolving the bottom features as viewed through the complex and varying optical properties of the water column is the central problem in coastal remote sensing. This requires hyperspectral imaging. There are three factors to estimate: water depth, bottom reflectance, and water clarity. Results demonstrate one approach to resolve this complexity using the additional information available in hyperspectral data. An example is given using data from the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS). Future directions for processing these data and the implications for the design of future systems for imaging the coastal ocean are discussed.

[1]  D. Lyzenga Passive remote sensing techniques for mapping water depth and bottom features. , 1978, Applied optics.

[2]  R. W. Austin,et al.  Nimbus-7 Coastal Zone Color Scanner: System Description and Initial Imagery , 1980, Science.

[3]  W. Philpot Radiative transfer in stratified waters: a single-scattering approximation for irradiance. , 1987, Applied optics.

[4]  Wallace M. Porter,et al.  A System Overview Of The Airborne Visible/Infrared Imaging Spectrometer (Aviris) , 1987, Optics & Photonics.

[5]  W. Philpot,et al.  Bathymetric mapping with passive multispectral imagery. , 1989, Applied Optics.

[6]  Wallace M. Porter,et al.  The airborne visible/infrared imaging spectrometer (AVIRIS) , 1993 .

[7]  C. Davis,et al.  Model for the interpretation of hyperspectral remote-sensing reflectance. , 1994, Applied optics.

[8]  André Morel,et al.  Diffuse reflectance of oceanic shallow waters: influence of water depth and bottom albedo , 1994 .

[9]  A. J. M. Zainal,et al.  New technique for enhancing the detection and classification of shallow marine habitats , 1994 .

[10]  R. Holyer,et al.  Coastal bathymetry from hyperspectral observations of water radiance , 1998 .

[11]  C. Mobley,et al.  Hyperspectral remote sensing for shallow waters. I. A semianalytical model. , 1998, Applied optics.

[12]  Curtiss O. Davis,et al.  Naval EarthMap Observer (NEMO) satellite , 1999, Optics & Photonics.

[13]  C. Mobley,et al.  Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization. , 1999, Applied optics.

[14]  Roland Doerffer,et al.  Neural network for emulation of an inverse model: operational derivation of Case II water properties from MERIS data , 1999 .

[15]  Z. Ahmad,et al.  Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. , 2000, Applied optics.

[16]  Kendall L. Carder,et al.  Properties of the Water Column and Bottom Derived from AVIRIS Data , 2001 .

[17]  Zhongping Lee,et al.  Effect of spectral band numbers on the retrieval of water column and bottom properties from ocean color data. , 2002, Applied optics.