scholarly journals Improving the Atmospheric Correction of OLCI over Turbid Waters by Using the SWIR band at 1016 nm and a new Baseline Residual Technique

2018 ◽  
Author(s):  
Juan Ignacio Gossn ◽  
Kevin G. Ruddick ◽  
Ana I. Dogliotti ◽  
Ana L. Delgado
2019 ◽  
Vol 11 (3) ◽  
pp. 220 ◽  
Author(s):  
Juan Gossn ◽  
Kevin Ruddick ◽  
Ana Dogliotti

A common approach to the pixel-by-pixel atmospheric correction of satellite water colour imagery is to calculate aerosol and water reflectance at two spectral bands, typically in the near infra-red (NIR, 700–1000 nm) or the short-wave-infra-red (SWIR, 1000–3000 nm), and then extrapolate aerosol reflectance to shorter wavelengths. For clear waters, this can be achieved simply for NIR bands, where the water reflectance can be assumed negligible i.e., the “black water” assumption. For moderately turbid waters, either the NIR water reflectance, which is non-negligible, must be modelled or longer wavelength SWIR bands, with negligible water reflectance, must be used. For extremely turbid waters, modelling of non-zero NIR water reflectance becomes uncertain because the spectral slopes of water and aerosol reflectance in the NIR become similar, making it difficult to distinguish between them. In such waters the use of SWIR bands is definitely preferred and the use of the MODIS bands at 1240 nm and 2130 nm is clearly established although, on many sensors such as the Ocean and Land Colour Instrument (OLCI), such SWIR bands are not included. Instead, a new, cheaper SWIR band at 1016 nm is available on OLCI with potential for much better atmospheric correction over extremely turbid waters. That potential is tested here. In this work, we demonstrate that for spectrally-close band triplets (such as OLCI bands at 779–865–1016 nm), the Rayleigh-corrected reflectance of the triplet’s “middle” band after baseline subtraction (or baseline residual, BLR) is essentially independent of the atmospheric conditions. We use the three BLRs defined by three consecutive band triplets of the group of bands 620–709–779–865–1016 nm to calculate water reflectance and hence aerosol reflectance at these wavelengths. Comparison with standard atmospheric correction algorithms shows similar performance in moderately turbid and clear waters and a considerable improvement in extremely turbid waters.


2011 ◽  
Vol 115 (8) ◽  
pp. 1955-1965 ◽  
Author(s):  
Cédric Jamet ◽  
Hubert Loisel ◽  
Christopher P. Kuchinke ◽  
Kevin Ruddick ◽  
Giuseppe Zibordi ◽  
...  

2020 ◽  
Vol 12 (22) ◽  
pp. 3791
Author(s):  
Jae-Hyun Ahn ◽  
Young-Je Park

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.


2018 ◽  
Vol 215 ◽  
pp. 18-32 ◽  
Author(s):  
Jianwei Wei ◽  
Zhongping Lee ◽  
Rodrigo Garcia ◽  
Laura Zoffoli ◽  
Roy A. Armstrong ◽  
...  

2021 ◽  
Vol 13 (6) ◽  
pp. 1050
Author(s):  
Juan Ignacio Gossn ◽  
Robert Frouin ◽  
Ana Inés Dogliotti

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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