Kevin George Ruddick

Bio: Kevin George Ruddick is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: SeaWiFS & Radiance. The author has an hindex of 1, co-authored 1 publications receiving 519 citations.

Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters

Abstract: The standard SeaWiFS atmospheric correction algorithm, designed for open ocean water, has been extended for use over turbid coastal and inland waters. Failure of the standard algorithm over turbid waters can be attributed to invalid assumptions of zero water-leaving radiance for the near-infrared bands at 765 and 865 nm. In the present study these assumptions are replaced by the assumptions of spatial homogeneity of the 765:865-nm ratios for aerosol reflectance and for water-leaving reflectance. These two ratios are imposed as calibration parameters after inspection of the Rayleigh-corrected reflectance scatterplot. The performance of the new algorithm is demonstrated for imagery of Belgian coastal waters and yields physically realistic water-leaving radiance spectra. A preliminary comparison with in situ radiance spectra for the Dutch Lake Markermeer shows significant improvement over the standard atmospheric correction algorithm. An analysis is made of the sensitivity of results to the choice of calibration parameters, and perspectives for application of the method to other sensors are briefly discussed. © 2000 Optical Society of America OCIS codes: 010.1290, 010.4450, 120.0280.

Bottom-up ecosystem trophic dynamics determine fish production in the Northeast Pacific.

Abstract: We addressed the question of bottom-up versus top-down control of marine ecosystem trophic interactions by using annual fish catch data and satellite-derived (SeaWiFS) chlorophyll a measurements for the continental margin of western North America. Findings reveal a marked alongshore variation in retained primary production that is highly correlated with the alongshore variation in resident fish yield. The highest productivity occurs off the coasts of Washington and southern British Columbia. Zooplankton data for coastal British Columbia confirm strong bottom-up trophic linkages between phytoplankton, zooplankton, and resident fish, extending to regional areas as small as 10,000 square kilometers.

Atmospheric correction of satellite ocean color imagery: the black pixel assumption

Abstract: The assumption that values of water-leaving radiance in the near-infrared (NIR) are negligible enable aerosol radiative properties to be easily determined in the correction of satellite ocean color imagery. This is referred to as the black pixel assumption. We examine the implications of the black pixel assumption using a simple bio-optical model for the NIR water-leaving reflectance [rho(w)(lambda(NIR))](N). In productive waters [chlorophyll (Chl) concentration >2 mg m(-3)], estimates of [rho(w)(lambda(NIR))](N) are several orders of magnitude larger than those expected for pure seawater. These large values of [rho(w)(lambda(NIR))](N) result in an overcorrection of atmospheric effects for retrievals of water-leaving reflectance that are most pronounced in the violet and blue spectral region. The overcorrection increases dramatically with Chl, reducing the true water-leaving radiance by roughly 75% when Chl is equal to 5 mg m(-3). Relaxing the black pixel assumption in the correction of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite ocean color imagery provides significant improvements in Chl and water-leaving reflectance retrievals when Chl values are greater than 2 mg m(-3). Improvements in the present modeling of [rho(w)(lambda(NIR))](N) are considered, particularly for turbid coastal waters. However, this research shows that the effects of nonzero NIR reflectance must be included in the correction of satellite ocean color imagery.

Sensor capability and atmospheric correction in ocean colour remote sensing

Abstract: Accurate correction of the corrupting effects of the atmosphere and the water’s surface are essential in order to obtain the optical, biological and biogeochemical properties of the water from satellite-based multi- and hyper-spectral sensors. The major challenges now for atmospheric correction are the conditions of turbid coastal and inland waters and areas in which there are strongly-absorbing aerosols. Here, we outline how these issues can be addressed, with a focus on the potential of new sensor technologies and the opportunities for the development of novel algorithms and aerosol models. We review hardware developments, which will provide qualitative and quantitative increases in spectral, spatial, radiometric and temporal data of the Earth, as well as measurements from other sources, such as the Aerosol Robotic Network for Ocean Color (AERONET-OC) stations, bio-optical sensors on Argo (Bio–Argo) floats and polarimeters. We provide an overview of the state of the art in atmospheric correction algorithms, highlight recent advances and discuss the possible potential for hyperspectral data to address the current challenges.

The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing

Abstract: A method of ocean color data processing using the combined near-infrared (NIR) and shortwave infrared (SWIR) bands for atmospheric correction for the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua is proposed. MODIS-Aqua has been producing the high quality ocean color products in the open oceans, but there are still some significant errors in the derived products in the coastal regions. With the proposed NIR-SWIR combined algorithm, MODIS ocean color data can be processed using the standard (NIR) atmospheric correction algorithm for the open oceans, whereas for the turbid waters in the coastal region the SWIR atmospheric correction algorithm can be executed. The turbid water index developed by Shi and Wang (2007) (Remote Sens. Environ. 110, 149-161 (2007)) is computed prior to the atmospheric correction for the identification of the productive and/or turbid waters where the SWIR algorithm can be operated. For non-turbid ocean waters (discriminated using the turbid water index criterion), the MODIS data are still processed using the standard (NIR) algorithm. The NIR-SWIR combined algorithm has been tested and evaluated. Two examples from MODIS-Aqua measurements along the U.S. and China east coast regions show improved ocean color products with the new approach. In particular, there are no obvious data discontinuities between using the NIR and SWIR methods. Therefore, with the NIR-SWIR combined approach for the MODIS ocean color data processing, good quality ocean color products can be derived both in clear (open) oceans as well as for turbid coastal waters.