Atmospheric correction algorithm based on vector radiative transfer modeling for hyperspectral remote sensing of ocean color

1999 ◽  
Author(s):  
Bo-Cai Gao ◽  
Marcos J. Montes ◽  
Ziauddin Ahmad ◽  
Curtiss O. Davis
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Hyperspectral Remote Sensing ◽  
Correction Algorithm ◽  
Radiative Transfer Modeling

Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space

2000 ◽  
Vol 39 (6) ◽  
pp. 887 ◽  
Author(s):  
Bo-Cai Gao ◽  
Marcos J. Montes ◽  
Ziauddin Ahmad ◽  
Curtiss O. Davis
Keyword(s):  
Remote Sensing ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Hyperspectral Remote Sensing ◽  
Correction Algorithm

Hyperspectral Remote Sensing and Radiative Transfer Simulation as a Tool for Monitoring Coral Reef Health

2002 ◽  
Vol 36 (1) ◽  
pp. 4-13 ◽  
Author(s):  
Hiroya Yamano ◽  
Masayuki Tamura ◽  
Yoshimitsu Kunii ◽  
Michio Hidaka
Keyword(s):  
Remote Sensing ◽  
Coral Reef ◽  
Radiative Transfer ◽  
Feasibility Studies ◽  
Hyperspectral Remote Sensing ◽  
Hyperspectral Data ◽  
Dead Coral ◽  
Hyperspectral Sensors ◽  
Reef Health ◽  
Radiative Transfer Modeling

Recent advances in the remote sensing of coral reefs include hyperspectral remote sensing and radiative transfer modeling. Hyperspectral data can be regarded as continuous and the derivative spectroscopy is effective for extracting coral reef components, including sand, macroalgae, and healthy, bleached, recently dead, and old dead coral. Radiative transfer models are effective for feasibility studies of satellite or airborne remote sensing. Using these techniques, we simulate and analyze the apparent reflectance of coral reef benthic features associated with bleaching events, obtained by hyperspectral sensors on various platforms (ROV, boat, airplane, and satellite), and suggest that the coral reef health on reef flats can be discriminated precisely. Remote sensing using hyperspectral sensors should significantly contribute to mapping and monitoring coral reef health.

Ocean Color Hyperspectral Remote Sensing With High Resolution and Low Latency--The HYPSO-1 CubeSat Mission

2021 ◽  
pp. 1-19
Author(s):  
Mariusz E. Grotte ◽  
Roger Birkeland ◽  
Evelyn Honore-Livermore ◽  
Sivert Bakken ◽  
Joseph L. Garrett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Ocean Color ◽  
Hyperspectral Remote Sensing ◽  
Low Latency

scholarly journals Improvement of Atmospheric Correction of Satellite Sentinel-3/OLCI Data for Oceanic Waters in Presence of Sargassum

2022 ◽  
Vol 14 (2) ◽  
pp. 386
Author(s):  
Léa Schamberger ◽  
Audrey Minghelli ◽  
Malik Chami ◽  
François Steinmetz
Keyword(s):  
Near Infrared ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Correction Algorithm ◽  
Infrared Band ◽  
Economic Issues ◽  
Optical Signature ◽  
Color Data ◽  
The Caribbean ◽  
Satellite Ocean Color

The invasive species of brown algae Sargassum gathers in large aggregations in the Caribbean Sea, and has done so especially over the last decade. These aggregations wash up on shores and decompose, leading to many socio-economic issues for the population and the coastal ecosystem. Satellite ocean color data sensors such as Sentinel-3/OLCI can be used to detect the presence of Sargassum and estimate its fractional coverage and biomass. The derivation of Sargassum presence and abundance from satellite ocean color data first requires atmospheric correction; however, the atmospheric correction procedure that is commonly used for oceanic waters needs to be adapted when dealing with the occurrence of Sargassum because the non-zero water reflectance in the near infrared band induced by Sargassum optical signature could lead to Sargassum being wrongly identified as aerosols. In this study, this difficulty is overcome by interpolating aerosol and sunglint reflectance between nearby Sargassum-free pixels. The proposed method relies on the local homogeneity of the aerosol reflectance between Sargassum and Sargassum-free areas. The performance of the adapted atmospheric correction algorithm over Sargassum areas is evaluated. The proposed method is demonstrated to result in more plausible aerosol and sunglint reflectances. A reduction of between 75% and 88% of pixels showing a negative water reflectance above 600 nm were noticed after the correction of the several images.

Effects of Earth curvature on atmospheric correction for ocean color remote sensing

2018 ◽  
Vol 209 ◽  
pp. 118-133 ◽  
Author(s):  
Xianqiang He ◽  
Knut Stamnes ◽  
Yan Bai ◽  
Wei Li ◽  
Difeng Wang
Keyword(s):  
Remote Sensing ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Ocean Color Remote Sensing

A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Clouds

2019 ◽  
Vol 36 (2) ◽  
pp. 203-216 ◽  
Author(s):  
Jarred L. Burley ◽  
Steven T. Fiorino ◽  
Brannon J. Elmore ◽  
Jaclyn E. Schmidt
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Performance Metrics ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Atmospheric Correction ◽  
Atmospheric Conditions ◽  
Diffuse Transmission ◽  
Cloud Data ◽  
Atmospheric Propagation

Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.

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