Accession Number : ADA317774

Title :   Coastal Bathymetry from Hyperspectral Data.

Corporate Author : NAVAL RESEARCH LAB STENNIS SPACE CENTER MS PHYSICS AND COMPUTER SCIENCES SEC TION

Personal Author(s) : Sandidge, Juanita C. ; Holyer, Ronald J.

PDF Url : ADA317774

Report Date : NOV 1995

Pagination or Media Count : 13

Abstract : A study is underway to investigate relationships of water depth, bottom type, and other optical variables to upwelling spectral radiance of coastal waters. A neural network and data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) are used to quantify these relationships. Data is analyzed for two areas: one on the western coast of Florida in Tampa Bay and the other on the Florida panhandle in Santa Rosa Sound. AVIRIS data from Tampa Bay is atmospherically corrected, whereas the data from the Santa Rosa Sound is not atmospherically corrected. The neural network can compute reasonable depths from spectral radiance in both cases. Sounding data obtained from the National Ocean Survey (NOS) hydrographic database is used in the training phase of the neural network and to test the accuracy of the result. Depths estimated by the neural network for Tampa Bay are accurate to a RMS error of 3.9 ft and for the Santa Rosa Sound to 3.0 fi. A crude bottom type classification of unknown accuracy emerged as a by-product of the investigation.

Descriptors :   *BATHYMETRY, *VISIBLE SPECTRA, *INFRARED SPECTRA, NEURAL NETS, COASTAL REGIONS, ACCURACY, RADIANCE, DATA REDUCTION, HYDROGRAPHY, FLORIDA, MULTISPECTRAL, UPWELLING, SOUNDING.

Subject Categories : Physical and Dynamic Oceanography
      Infrared Detection and Detectors

Distribution Statement : APPROVED FOR PUBLIC RELEASE