Atmospheric Correction Algorithm For Hyperspectral Remote Sensing Of Ocean Color From Space
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Atmospheric Correction Algorithm for Hyperspectral Remote Sensing of Ocean Color from Space
Existing atmospheric correction algorithms for multichannel remote sensing of ocean color from space were designed for retrieving water-leaving radiances in the visible over clear deep ocean areas and cannot easily be modified for retrievals over turbid coastal waters. We have developed an atmospheric correction algorithm for hyperspectral remote sensing of ocean color with the near-future Coastal Ocean Imaging Spectrometer. The algorithm uses lookup tables generated with a vector radiative transfer code. Aerosol parameters are determined by a spectrum-matching technique that uses channels located at wavelengths longer than 0.86 mm. The aerosol information is extracted back to the visible based on aerosol models during the retrieval of water-leaving radiances. Quite reasonable water-leaving radiances have been obtained when our algorithm was applied to process hyperspectral imaging data acquired with an airborne imaging spectrometer.
Hyperspectral Remote Sensing of Nearshore Water Quality
This book provides details on of the utility of hyperspectral remote sensing – NASA/AVIRIS in nearshore water quality issues of NY/NJ. It demonstrates the use of bio optical modeling and retrieval techniques to derive the concentrations of important water quality parameters (chlorophyll, color dissolved organic matter and suspended sediments) in the study area. The case study focuses on the nearshore waters of NY/NJ considered as a valued ecological, economic and recreational resource within the New York metropolitan area. During field campaigns (1998-2001) measurements were made to establish hydrological optical properties of the NY/NJ nearshore waters with concurrent NASA/AVIRIS overflights. The field measurements included: 1) concurrent above and below surface spectral reflectance; 2) shipboard sampling for determination of inherent optical properties (IOP); and 3) concentrations of optically important water quality parameters. Understanding the relationship between reflectance, absorption and scattering is essential for developing the analytical algorithm necessary to use remote sensing as a monitoring /management tool in the nearshore environment.
Hyperspectral Imaging Remote Sensing
Author: Dimitris G. Manolakis
language: en
Publisher: Cambridge University Press
Release Date: 2016-10-20
Understand the seminal principles, current techniques, and tools of imaging spectroscopy with this self-contained introductory guide.