Retrieval of marine water constituents from AVIRIS data in the Hudson/Raritan Estuary

Abstract

This paper reports on the validation of bio‐optical models in estuarine and nearshore (case 2) waters of New Jersey–New York to retrieve accurate water leaving radiance spectra and chlorophyll concentration from the NASA Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data complemented with in situ measurements. The study area—Hudson/Raritan Estuary—is a complex estuarine system where tidal and wind‐driven currents are modified by freshwater discharges from the Hudson, Raritan, Hackensack, and Passaic rivers. Over the last century the estuarine water quality has degraded, in part due to eutrophication, which has disrupted the pre‐existing natural balance, resulting in phytoplankton blooms of both increased frequency and intensity, increasing oxygen demand and leading to episodes of hypoxia. During 1999–2001 data acquisitions by NASA AVIRIS field measurements were obtained to establish hydrological optical properties of the Hudson/Raritan Estuary: (1) concurrent above‐ and below‐surface spectral irradiance; (2) sampling for laboratory determination of inherent optical properties; and (3) concentrations of optically‐important water quality parameters. We used a bio‐optical model based on Gordon et al. to predict the sub‐surface irradiance reflectance from optically important water constituents. Modelling of reflectance is a prerequisite for processing remote sensing data to desired thematic maps for input into the geographical information system (GIS) for use as a management tool in water quality assessment. A Radiative Transfer Code—MODTRAN‐4—was applied to remove the effects of the atmosphere so as to infer the water leaving radiance from the AVIRS data. The results of this procedure were not satisfactory, therefore an alternative approach was tested to directly correct the AVIRIS image using modelled spectra based on measured optical characteristics. The atmospherically corrected AVIRIS ratio image was used to calculate a thematic map of water quality parameters (i.e. chlorophyll‐a) concentration, which subsequently were integrated into a GIS for management of water quality purposes.