Next Article in Journal
A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products
Previous Article in Journal
A Method for Detection of Small Moving Objects in UAV Videos
Article

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

1
Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
2
ACRI-ST, 260 Route du Pin Montard, BP 234, 06904 Sophia-Antipolis, France
3
Serco Italia SpA, Via Sciadonna 24-26, 00044 Frascati, Italy
4
European Space Agency Centre for Earth Observation (ESA-ESRIN), Largo Galileo Galilei, 1, 00044 Frascati, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(4), 654; https://doi.org/10.3390/rs13040654
Received: 14 December 2020 / Revised: 4 February 2021 / Accepted: 4 February 2021 / Published: 11 February 2021
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
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. View Full-Text
Keywords: atmospheric correction; iCOR; surface reflectance; Sentinel-3; OLCI; AERONET; 6SV; SYN L2; RadCalNet atmospheric correction; iCOR; surface reflectance; Sentinel-3; OLCI; AERONET; 6SV; SYN L2; RadCalNet
Show Figures

Graphical abstract

MDPI and ACS Style

Wolters, E.; Toté, C.; Sterckx, S.; Adriaensen, S.; Henocq, C.; Bruniquel, J.; Scifoni, S.; Dransfeld, S. iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2. Remote Sens. 2021, 13, 654. https://doi.org/10.3390/rs13040654

AMA Style

Wolters E, Toté C, Sterckx S, Adriaensen S, Henocq C, Bruniquel J, Scifoni S, Dransfeld S. iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2. Remote Sensing. 2021; 13(4):654. https://doi.org/10.3390/rs13040654

Chicago/Turabian Style

Wolters, Erwin, Carolien Toté, Sindy Sterckx, Stefan Adriaensen, Claire Henocq, Jérôme Bruniquel, Silvia Scifoni, and Steffen Dransfeld. 2021. "iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2" Remote Sensing 13, no. 4: 654. https://doi.org/10.3390/rs13040654

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop