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http://dx.doi.org/10.7780/kjrs.2022.38.5.1.16

Atmospheric Correction of Sentinel-2 Images Using GK2A AOD: A Comparison between FLAASH, Sen2Cor, 6SV1.1, and 6SV2.1  

Kim, Seoyeon (Geomatics Research Institute, Pukyong National University)
Youn, Youjeong (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Jeong, Yemin (Geomatics Research Institute, Pukyong National University)
Park, Chan-Won (High-tech Agro-Materials Promotion Team, Rural Development Administration)
Na, Sang-Il (Climate Change Assessment Division, Department of Agricultural Environment, National Institute of Agricultural Sciences)
Ahn, Hoyong (Climate Change Assessment Division, Department of Agricultural Environment, National Institute of Agricultural Sciences)
Ryu, Jae-Hyun (Climate Change Assessment Division, Department of Agricultural Environment, National Institute of Agricultural Sciences)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.38, no.5_1, 2022 , pp. 647-660 More about this Journal
Abstract
To prepare an atmospheric correction model suitable for CAS500-4 (Compact Advanced Satellite 500-4), this letter examined an atmospheric correction experiment using Sentinel-2 images having similar spectral characteristics to CAS500-4. Studies to compare the atmospheric correction results depending on different Aerosol Optical Depth (AOD) data are rarely found. We conducted a comparison of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Sen2Cor, and Second Simulation of the Satellite Signal in the Solar Spectrum - Vector (6SV) version 1.1 and 2.1, using Geo-Kompsat 2A (GK2A) Advanced Meteorological Imager (AMI) and Aerosol Robotic Network (AERONET) AOD data. In this experiment, 6SV2.1 seemed more stable than others when considering the correlation matrices and the output images for each band and Normalized Difference Vegetation Index (NDVI).
Keywords
Atmospheric correction; CAS500-4; Sentinel-2; GK2A; FLAASH; Sen2Cor; 6SV;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 ESA (European Space Agency), 2021. Sen2Cor Software Release Note, http://step.esa.int/thirdparties/sen2cor/2.10.0/docs/S2-PDGS-MPC-L2A-SRN-V2.10.0.pdf, Accessed on Sep. 18, 2022.
2 Lee, K.S., C.S. Lee, M. Seo, S. Choi, N.H. Seong, D. Jin, J.M. Yeom, and K.S. Han, 2020. Improvements of 6S look-up-table based surface reflectance employing minimum curvature surface method, Asia-Pacific Journal of Atmospheric Sciences, 56(2): 235-248. https://doi.org/10.1007/s13143-019-00164-3   DOI
3 Proud, S.R., M.O. Rasmussen, R. Fensholt, I. Sandholt, C. Shisanya, W. Mutero, C. Mbow, and A. Anyamba, 2010. Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data, Remote Sensing of Environment, 114(8): 1687-1698. https://doi.org/10.1016/j.rse.2010.02.020   DOI
4 Cooley T., G.P. Anderson, G.W. Felde, M.L. Hoke, A.J. Ratkowski, J.H. Chetwynd, J.A. Gardner, S.M. Adler-Golden, M.W. Matthew, A. Berk, L.S. Bernstein, P.K. Acharya, D. Miller, and P. Lewis, 2002. FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation, Proc. of IEEE International Geoscience and Remote Sensing Symposium, Toronto, ON, Canada, Jun. 24-28, vol. 3, pp. 1414-1418. https://doi.org/10.1109/IGARSS.2002.1026134   DOI
5 Eck, T.F., B.N. Holben, J.S. Reid, Q. Dubovik, A. Smirnov, N.T. O'Neill, I. Slutsker, and S. Kinne, 1999. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, Journal of Geophysical Research: Atmospheres, 104(D24): 31333-31349. https://doi.org/10.1029/1999JD900923   DOI
6 Kinne, S., M. Schulz, C. Textor, S. Guibert, Y. Balkanski, S.E. Bauer, T. Berntsen, T.F. Berglen, Q. Boucher, M. Chin, W. Collins, F. Dentener, T. Diehl, R. Easter, J. Feichter, D. Fillmore, S. Ghan, P. Ginoux, S. Gong, A. Grini, J. Hendricks, M. Herzog, L. Horowitz, I. Isaksen, T. Iversen, A. Kirkevag, S. Kloster, D. Koch, J.E. Kristjansson, M. Krol, A. Lauer, J.F. Lamarque, G. Lesins, X. Liu, U. Lohmann, V. Montanaro, G. Myhre, J. Penner, G. Pitari, S. Reddy, O. Seland, P. Stier, T. Takemura, and X. Tie, 2006. An AeroCom initial assessment - optical properties in aerosol component modules of global models, Atmospheric Chemistry and Physics, 6(7): 1815-1834. https://doi.org/10.5194/acp-6-1815-2006   DOI
7 Lee, K.S., 2019. Atmospheric correction issues of optical imagery in land remote sensing, Korean Journal of Remote Sensing, 35(6-3): 1299-1312 (in Korean with English abstract). https://doi.org/10.7780/kjrs.2019.35.6.3.12   DOI
8 Martins, V.S., C.C.F. Barbosa, L.A.S. De Carvalho, D.S.F. Jorge, F.D.L. Lobo, and E.M.L.D.M. Novo, 2017. Assessment of atmospheric correction methods for Sentinel-2 MSI images applied to Amazon floodplain lakes, Remote Sensing, 9(4): 322-344. https://doi.org/10.3390/rs9040322   DOI
9 Vermote, E.F., D. Tanre, J.L. Deuze, M. Herman, and J.J. Morcette, 1997. Second simulation of the satellite signal in the solar spectrum, 6S: An overview, IEEE Transactions on Geoscience and Remote Sensing, 35(3): 675-686. https://doi.org/10.1109/36.581987   DOI
10 Prasad, A.K. and R.P. Singh, 2007. Comparison of MISR-MODIS aerosol optical depth over the Indo-Gangetic basin during the winter and summer seasons (2000-2005), Remote Sensing of Environment, 107(1-2): 109-119. https://doi.org/10.1016/j.rse.2006.09.026   DOI
11 Youn, Y. and Y. Lee, 2022. Spatial Gap-filling of GK-2A/AMI AOD products for Estimation of Particulate Matter using Machine Learning, Proc. of the 8th World Congress on New Technologies (NewTech'22), Prague, Czech Republic, Aug. 3-5, no. ICEPR 155. https://doi.org/10.11159/icepr22.155   DOI