Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables

Curtis D. Mobley, Lydia K. Sundman, Curtiss O. Davis, Jeffrey H. Bowles, Trijntje Valerie Downes, Robert A. Leathers, Marcos J. Montes, William Paul Bissett, David D.R. Kohler, Ruth Pamela Reid, Eric M. Louchard, Arthur Gleason

Research output: Contribution to journalArticlepeer-review

222 Scopus citations


A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured Rrs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.

Original languageEnglish (US)
Pages (from-to)3576-3592
Number of pages17
JournalApplied Optics
Issue number17
StatePublished - Jun 10 2005

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering


Dive into the research topics of 'Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables'. Together they form a unique fingerprint.

Cite this