scholarly journals Atmospheric Correction of GOCI Using Quasi-Synchronous VIIRS Data in Highly Turbid Coastal Waters

2019 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Jie Wu ◽  
Chuqun Chen ◽  
Sravanthi Nukapothula
Keyword(s):  
Coastal Waters ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Turbid Waters ◽  
Aerosol Scattering ◽  
Temporal And Spatial ◽  
Shortwave Infrared ◽  
The Western Pacific

The Geostationary Ocean Color Imager (GOCI) sensor, with high temporal and spatial resolution (eight images per day at an interval of 1 hour, 500 m), is the world’s first geostationary ocean color satellite sensor. GOCI provides good data for ocean color remote sensing in the Western Pacific, among the most turbid waters in the world. However, GOCI has no shortwave infrared (SWIR) bands making atmospheric correction (AC) challenging in highly turbid coastal regions. In this paper, we have developed a new AC algorithm for GOCI in turbid coastal waters by using quasi-synchronous Visible Infrared Imaging Radiometer Suite (VIIRS) data. This new algorithm estimates and removes the aerosol scattering reflectance according to the contributing aerosol models and the aerosol optical thickness estimated by VIIRS’s near-infrared (NIR) and SWIR bands. Comparisons with other AC algorithms showed that the new algorithm provides a simple, effective, AC approach for GOCI to obtain reasonable results in highly turbid coastal waters.

scholarly journals Shortwave Infrared Imaging with J-Aggregates Stabilized in Hollow Mesoporous Silica Nanoparticles

2018 ◽  
Author(s):  
Wei Chen ◽  
ChiAn Cheng ◽  
Emily Cosco ◽  
Shyam Ramakrishnan ◽  
Jakob Lingg ◽  
...  
Keyword(s):  
Mesoporous Silica ◽  
Contrast Agents ◽  
Silica Nanoparticles ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Mesoporous Silica Nanoparticles ◽  
J Aggregates ◽  
Hollow Mesoporous Silica ◽  
Shortwave Infrared

Tissue is translucent to shortwave infrared (SWIR) light, rendering optical imaging superior in this region. However, the widespread use of optical SWIR imaging has been limited, in part, by the lack of bright, biocompatible contrast agents that absorb and emit light above 1000 nm. J-aggregation offers a means to transform stable, near-infrared (NIR) fluorophores into red-shifted SWIR contrast agents. Here we demonstrate that hollow mesoporous silica nanoparticles (HMSNs) can template the J-aggregation of NIR fluorophore IR-140 to result in nanomaterials that absorb and emit SWIR light. The J-aggregates inside PEGylated HMSNs are stable for multiple weeks in buffer and enable high resolution imaging <i>in vivo</i>with 980 nm excitation.

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.

scholarly journals Assessment of the Number of Valid Observations and Diurnal Changes in Chl-a for GOCI: Highlights for Geostationary Ocean Color Missions

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3377
Author(s):  
Dan Zhao ◽  
Lian Feng
Keyword(s):  
Ocean Color ◽  
Inland Waters ◽  
Diurnal Changes ◽  
Satellite Mission ◽  
Pronounced Difference ◽  
Chl A ◽  
Spatial Domains ◽  
The Mean ◽  
Temporal And Spatial ◽  
The Western Pacific

The first geostationary ocean color satellite mission (geostationary ocean color imager, or GOCI) has provided eight hourly observations per day over the western Pacific region since June 2010. GOCI imagery has been widely used to track the short-term dynamics of coastal and inland waters. Few studies have been performed to comprehensively assess the advantages of GOCI images in obtaining valid observations and estimating diurnal changes within the water column. Using the entire mission dataset between 2011 and 2017, these knowledge gaps were filled by comparing the daily percentages of valid observations (DPVOs) between GOCI and MODIS Aqua (MODISA) and by examining the diurnal changes in Chl-a over the East China Sea. The mean DPVOs of GOCI was 152.6% over the clear open ocean, suggesting that a daily valid coverage could be expected with GOCI. The GOCI DPVOs were ~26 times greater than the MODISA DPVOs; this pronounced difference was caused by the combined effects of their different observational frequencies and the more conservative quality flag system for MODISA. Diurnal changes in the GOCI-derived Chl-a were also found, with generally higher Chl-a in the afternoon than the morning and pronounced heterogeneities in the temporal and spatial domains. However, whether such diurnal changes are due to the real dynamics of the oceanic waters or artifacts of the satellite retrievals remains to be determined. This study provides the first comprehensive quantification of the unparalleled advantages of geostationary ocean color missions over polar orbiters, and the results highlights the importance of geostationary ocean color missions in studying coastal and inland waters.

scholarly journals Estimating Water Reflectance at Near-Infrared Wavelengths for Turbid Water Atmospheric Correction: A Preliminary Study for GOCI-II

2020 ◽  
Vol 12 (22) ◽  
pp. 3791
Author(s):  
Jae-Hyun Ahn ◽  
Young-Je Park
Keyword(s):  
Near Infrared ◽  
Accurate Result ◽  
Atmospheric Correction ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Absolute Percentage Error ◽  
Turbid Waters ◽  
The Mean ◽  
Relationship Of ◽  
Spectral Relationship

Atmospheric correction is a fundamental process to remove the atmospheric effect from the top-of-atmosphere level. The atmospheric correction algorithm developed by the Korea Institute of Ocean Science and Technology employs a near-infrared (NIR) water reflectance model to deal with non-negligible NIR water reflectance over turbid waters. This paper describes the NIR water reflectance models using visible bands of the Second Geostationary Ocean Color Imager (GOCI-II). Whereas the previous GOCI uses the 660 nm band to estimate NIR water reflectance (SR660), GOCI-II uses additional 620 and 709 nm bands, which improves estimation of NIR water reflectance. We developed two reflectance models with the additional bands based on a spectral relationship of water reflectance (SR709) and a spectral relationship of inherent optical properties (SRIOP) from red to NIR wavelengths. A preliminary validation of these two reflectance models was performed using both simulations and an in situ dataset. The validation result showed that the mean absolute percentage error of the SR709 model compared with SR660 was reduced by approximately 6% and 10% at 745 and 865 nm, respectively. Moreover, the mean absolute percentage error of the SRIOP model compared with SR660 was reduced by approximately 12% and 16% at 745 and 865 nm, respectively. Note that SR709 produces the most accurate result when there is only one sediment type, and SRIOP shows the most accurate result when various sediment types exist. Users will be able to optionally select the appropriate NIR water reflectance models in the GOCI-II atmospheric correction process to enhance the accuracy of aerosol reflectance correction over turbid waters.

scholarly journals Non-invasive monitoring of chronic liver disease via near-infrared and shortwave-infrared imaging of endogenous lipofuscin

2020 ◽  
Vol 4 (8) ◽  
pp. 801-813 ◽  
Author(s):  
Mari Saif ◽  
Wilhelmus J. Kwanten ◽  
Jessica A. Carr ◽  
Ivy X. Chen ◽  
Jessica M. Posada ◽  
...  
Keyword(s):  
Liver Disease ◽  
Chronic Liver Disease ◽  
Near Infrared ◽  
Infrared Imaging ◽  
Chronic Liver ◽  
Invasive Monitoring ◽  
Non Invasive ◽  
Shortwave Infrared

Preliminary Evaluation of the Atmospheric Correction Look-Up-Tables (LUTs) of the COCTS-HY1C

2020 ◽  
Author(s):  
Keping Du ◽  
Shuguo Chen ◽  
Jing Ding ◽  
Zhongping Lee
Keyword(s):  
Rayleigh Scattering ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Ultra Violet ◽  
Preliminary Evaluation ◽  
The Novel ◽  
Aerosol Scattering ◽  
Processing Step ◽  
Color Sensors ◽  
The Look

&lt;p&gt;The Chinese Ocean Colour and Temperature Scanner (COCTS), Coastal Zone Imager (CZI) and the novel Ultra-Violet Imager (UVI) which on-board the Chinese Ocean Satellite&amp;#160; HY-1C was launched in September 2018. The atmospheric correction of ocean color sensors was a critical step for accurate retrieval of the remote sensing reflectance, and the look-up-tables (LUTs), for the Rayleigh scattering, the aerosol scattering, and the diffuse transmittance, which were built bases on a Successive Order Scattering Vector Radiative Transfer Solver, played an important role in the processing step. Preliminary evaluation has been performed using the SeaWiFS LUTs and the MODIS data, it showed that COCTS can provide accurate ocean color products.&lt;/p&gt;

Atmospheric Correction of Satellite Optical Imagery over the Río de la Plata Highly Turbid Waters Using a SWIR-Based Principal Component Decomposition Technique

2021 ◽  
Vol 13 (6) ◽  
pp. 1050
Author(s):  
Juan Ignacio Gossn ◽  
Robert Frouin ◽  
Ana Inés Dogliotti
Keyword(s):  
Principal Components ◽  
Near Infrared ◽  
Atmospheric Correction ◽  
Low Noise ◽  
Optical Data ◽  
Rio De La Plata ◽  
Río De La Plata ◽  
La Plata ◽  
Turbid Waters ◽  
The Impact

Estimating water reflectance accurately from satellite optical data requires implementing an accurate atmospheric correction (AC) scheme, a particularly challenging task over optically complex water bodies, where the signal that comes from the water prevents using the near-infrared (NIR) bands to separate the perturbing atmospheric signal. In the present work, we propose a new AC scheme specially designed for the Río de la Plata—a funnel-shaped estuary in the Argentine–Uruguayan border—highly scattering turbid waters. This new AC scheme uses far shortwave infrared (SWIR) bands but unlike previous algorithms relates the atmospheric signal in the SWIR to the signal in the near-infrared (NIR) and visible (VIS) bands based on the decomposition into principal components of the atmospheric signal. We describe the theoretical basis of the algorithm, analyze the spectral features of the simulated principal components, theoretically address the impact of noise on the results, and perform match-ups exercises using in situ measurements and Moderate Resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) imagery over the region. Plausible water reflectance retrievals were obtained in the NIR and VIS bands from both simulations and match-ups using field data—with better performance (i.e., lowest errors and offsets, and slopes closest to 1) compared to existing AC schemes implemented in the NASA Data Analysis Software (SeaDAS). Moreover, retrievals over images in the VIS and NIR bands showed low noise, and the correlation was low between aerosol and water reflectance spatial fields.

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