Development of a new image based atmospheric correction algorithm for aerosol optical thickness retrieval using the darkest pixel method

2012 ◽  
Vol 6 (1) ◽  
pp. 063538 ◽  
Author(s):  
Diofantos G. Hadjimitsis
Keyword(s):  
Optical Thickness ◽  
Atmospheric Correction ◽  
Aerosol Optical Thickness ◽  
Correction Algorithm

scholarly journals iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2

2021 ◽  
Vol 13 (4) ◽  
pp. 654
Author(s):  
Erwin Wolters ◽  
Carolien Toté ◽  
Sindy Sterckx ◽  
Stefan Adriaensen ◽  
Claire Henocq ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Negative Bias ◽  
Surface Reflectance ◽  
Temporal Consistency ◽  
Correction Algorithm ◽  
Land Surfaces ◽  
Relative Differences ◽  
Level 2

To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences < ±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI “excess of brightness”. The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR’s higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations.

scholarly journals Simultaneous determination of aerosol optical thickness and water leaving radiance from multispectral measurements in coastal waters

2017 ◽  
Author(s):  
Chong Shi ◽  
Teruyuki Nakajima
Keyword(s):  
Simultaneous Determination ◽  
Optical Thickness ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Ocean Surface ◽  
Aerosol Optical Thickness ◽  
Surface Model ◽  
Spectral Measurements ◽  
Mean Square Errors

Abstract. Retrieval of aerosol optical properties and water leaving radiance over ocean is changeling since the latter mostly accounts for ~10% of satellite observed signal and can be easily contaminated by the atmospheric scattering. Such an effort would be more difficulty in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water leaving radiance (nLw) from multi-spectral measurements. In this algorithm, a coupled atmosphere-ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite observed reflectance at the top of atmosphere and water leaving radiance just above the ocean surface. Then a full-physical nonlinear optimization method is adopted to retrieve AOT and nLw in one step. The algorithm is validated using Aerosol Robotic Network Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observation cases covered both in and out of sun glint from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements in each site. It is demonstrated that more accurate AOT are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sun glint conditions, where the averaged percentage difference (APD) of retrieved AOT generally reduce by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme. It is caused that all the spectral measurements can be used jointly to increase the information content in the inversion of AOT and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, over atmospheric correction can be avoided to have a significant improvement for the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443)/nLw(554) and nLw(488)/nLw(554), which are employed in the inversion of chlorophyll a concentration (Chl), are obtained using simultaneous retrieval approach with less root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as a result that the APD value of retrieved Chl decreases by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of oceanic bio-optical module of current model.

scholarly journals AEROSOL PLUMES CHARACTERIZATION BY HYPERSPECTRAL IMAGES COUPLED WITH SENTINEL-2 PRODUCTS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 791-797
Author(s):  
G. Calassou ◽  
P.-Y. Foucher ◽  
J.-F. Leon
Keyword(s):  
Optical Thickness ◽  
Atmospheric Correction ◽  
Principal Component ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Multispectral Data ◽  
The Difference ◽  
Industrial Aerosol ◽  
Sentinel 2

Abstract. In this paper, we focus on the retrieval of microphysical and optical properties of industrial aerosol plumes through a process using airborne hyperspectral and Sentinel-2 multi-spectral images. The process allows first to perform atmospheric correction and second to determine background aerosols thanks to a comparison between hyperspectral and Sentinel-2 reflectances. Hyperspectral methodologies use the radiance differential between the measurement in the plume and the corresponding measurements out of the plume to estimate plume properties. To retrieve the surface reflectance under the plume, a principal component analysis coupling hyperspectral and multispectral data class by class is achieved. The developed method aims to compare the difference between measured and estimated reflectance with a radiative transfer model accounting for plume properties (particle radius and aerosol optical thickness of the plume). We have applied the method to a steel plant in the south of France. The retrieved plume show an aerosol mean radius between 0.05 and 0.2 µm with a mean aerosol optical thickness about 0.05 along the plume.

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