Application of a Near-Infrared Slope Algorithm to Derive Optical Properties From High-Resolution, Hyperspectral Aircraft Imagery

摘要

Using new algorithms, we derive estimates of partitioned absorption (a) and scattering (b) coefficients from high-resolution, hyperspectral aircraft imagery collected with the PHILLS sensor. During May 2002, we conducted simultaneous ship and aircraft surveys in a dynamic environment in the northern Gulf of Mexico (coastal waters near Mobile Bay, Alabama). Optical measurements included hyperspectral remote sensing reflectance, partitioned absorption coefficients (phytoplankton, detrital, and colored dissolved organic matter components), beam attenuation (c), backscattering coefficient, HPLC phytoplankton pigment concentrations, and organic/inorganic particle loads. Our objectives arc to: (I) develop new algorithms to estimate optical properties from hyperspectral ocean color imagery; (2) apply to high-resolution aircraft imagery to characterize the spatial optical variability in an environment impacted by high concentrations of dissolved and particulate materials; and (3) perform an optical water mass classification on the aircraft imagery. The new optical classification system based on the partitioned absorption coefficients is used to distinguish water masses and track coastal features.