Continued Development of the Look-Up-Table Methodology for Interpretation of Remotely Sensed Ocean Color

Abstract

The LUT approach to inverting ocean color spectral remote- sensing data seeks to use the greater number of degrees of freedom available in the hyperspectral data to retrieve (1) bathymetry, (2) water column lOPs, and (3) bottom identification in optically-shallow waters. We have discovered several significant findings in developing this approach. First is that the quality of the input measured spectra is critical to the success of the technique. Thus, the characterization and calibration of the measurement sensors, as well as the accurate characterization of any environmental noise (e.g. atmospheric correction) is critical for success. Second, the best approach to this type of inversion is to use hybrid matching techniques that focus on total -magnitude of the measured signal, as well as spectral angle. Third, when perfection in calibration or removal of environmental noise is unattainable, the best approach uses a knowledge-based technique to refining the LUT search-. For example, in waters deeper than 2 meters, it may be useful to exempt wavelengths longer than 600 nm from the database search criteria so that residual skylight reflectance that has not been removed from the sensor measured radiance does not reduce the accuracy of the LUT retrievals.

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Document Details

Document Type
Technical Report
Publication Date
Jan 30, 2007
Accession Number
ADA462664

Entities

People

  • William Paul Bissett

Organizations

  • Florida Environmental Research Institute

Tags

Communities of Interest

  • Air Platforms
  • Cyber
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Chemistry
  • Data Sets
  • Databases
  • Detectors
  • Environment
  • Human Systems Integration
  • Hyperspectral Imagery
  • Information Operations
  • Military Operations
  • Military Research
  • Optical Properties
  • Optics
  • Radiative Transfer
  • Remote Sensing
  • Scattering
  • Shallow Water

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Coastal Oceanography
  • Systems Analysis and Design