Suspended particulate matter (SPM) significantly impacts water clarity, degrading underwater electro-optical detection systems. It is also comprised of the living, detrital, and minerogenic particles that contribute to oceanic biogeochemical cycling. Models designed to derive SPM from optical properties such as particulate backscattering and attenuation have been largely empirical in nature, i.e., simple linear relationships, and therefore fluctuate with varying particle composition. Consequently, such models perform well regionally and/or temporally, but their applicability is constrained. An analytical inversion model has been developed to quantitatively interpret scattering measurements in terms of SPM. The algorithm requires measurements of backscattering and spectral attenuation. These measurements can be made with commercial-off-the-shelf technology suitable for deployment on compact autonomous platforms, thus having the potential to dramatically increase spatial and temporal resolving capabilities for SPM. Recent work evaluates the role of particle size ranges in greater detail and assesses performance for multiple data sets including the GlobCOAST data set, a large, diverse data set of high quality SPM and optical property measurements.
The SIMBADA radiometer was designed to check the radiometric calibration of satellite ocean-color sensors and evaluate the atmospheric correction of ocean-color imagery. It measures marine reflectance and aerosol optical thickness in 11 spectral bands covering the spectral range 350 to 870 nm. Aerosol optical thickness is obtained by viewing the sun disk and marine reflectance by viewing the ocean surface through a vertical polarizer that minimizes
sun glint and reflected skylight. The measurements made by SIMBADA during ACE-Asia (March-April 2001, Japan Sea) and AOPEX (July-August 2004, Mediterranean Sea) are compared with those made concomitantly by other ocean radiometers and sun photometers, i.e., MER, PRR, SPMR, Trios, TSRB, and BOUSSOLE instruments for marine reflectance and CIMEL and Microtops for aerosol optical thickness. Agreement is generally good between the various measurements or estimates. The SIMBADA aerosol optical thickness is within ±0.02 of the values obtained by other sun photometers. The SIMBADA marine reflectance, after correction for bi-directional effects (Q factor), does not exhibit biases when compared with estimates by other radiometers, which generally agree within ±10%. In some cases larger discrepancies exist, and they are largely explained by differences in solar irradiance. More accurate SIMBADA estimates may be obtained by improving the radiometric calibration, the correction for angular geometry and water body polarization, the calculation of incident solar irradiance, and the selection of data minimally affected by sky reflection.
The fine-scale study of the diffuse attenuation coefficient, Kd(λ), of the spectral solar downward irradiance is only
feasible by ocean color remote sensing. Several empirical and semi-analytical methods exist. However, most of tthese
models are generally applicable for clear open ocean waters. They show limitations when applied to coastal waters. A
new empirical method based on neural networks has been developed using a relationship between the remote-sensing
reflectances between 412 and 670 nm and Kd(490), for the SeaWiFS ocean color remote sensor. The architecture of the
neural network has been defined using synthetical and in situ dataset and the optimal design is a tow hidden layer neural
network with 4 neurons of the first layer and three on the second layer. The comparison with the SeaWiFS empirical
algorithms shows similar retrievals accuracies for low values of Kd(490) (i.e. <0.20 m-1) and better estimates for greater
values of and Kd(490). The new model is suitable for open water but also for turbid waters and does not show the
limitations of the empirical method. The new model is more general that the empirical methods.
During spring and summer 2004, intensive field campaigns were conducted in the Eastern English Channel. This region is characterized by relatively intense phytoplankton blooms, low bathymetry, strong tide ranges and great river inputs. The sampling period accounts for episodic blooms of prymnesiophyceae Phaeocystis globosa and diatoms. Hyperspectral radiometric measurements (TRIOS; 350-950 nm, with a 3 nm spectral resolution) were concurrently performed with water sampling for biogeochemical and optical characterization. The remote sensing reflectance, Rrs, is analyzed in conjunction with variation of the water composition. We particularly focus on the capability to identify some phytoplankton species from Rrs in this very variable environment. Different methods, based on multispectral and hyperspectral data are tested and compared for that purpose. We show that no Rrs ratio allows to discriminate between diatoms and Phaeocystis. In contrast, the derivative analysis applied to hyperspectral data stresses large differences in some part of the Rrs spectra collected in diatoms or Phaeocystis dominated waters.
Conference Committee Involvement (7)
Active and Passive Remote Sensing of Oceans, Seas, and Lakes
2 December 2024 | Kaohsiung, Taiwan
Remote Sensing of the Open and Coastal Ocean and Inland Waters
24 September 2018 | Honolulu, Hawaii, United States
Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and Challenges
4 April 2016 | New Delhi, India
Ocean Remote Sensing and Monitoring from Space
15 October 2014 | Beijing, China
Remote Sensing of the Marine Environment II
31 October 2012 | Kyoto, Japan
Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment
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