63
Views
0
CrossRef citations to date
0
Altmetric
Research Letter

Improving atmospheric correction for KOMPSAT-3A by optimizing the 6SV look-up table

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon show all
Pages 514-525 | Received 12 Sep 2023, Accepted 30 Mar 2024, Published online: 20 Apr 2024

References

  • Berk, A., G. P. Anderson, P. K. Acharya, L. S. Bernstein, L. Muratov, J. Lee, M. Fox, et al. 2006. “MODTRAN5: 2006 update.” In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, Vol. 6233. 508–515. Bellingham, Washington USA: SPIE.
  • Bréon, F.-M., and E. Vermote. 2012. “Correction of MODIS Surface Reflectance Time Series for BRDF Effects.” Remote Sensing of Environment 125:1–9. https://doi.org/10.1016/j.rse.2012.06.025.
  • Cook, D. 2016. Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI. Sebastopol: O’Reilly Media, Inc.
  • Guanter, L., R. Richter, and H. Kaufmann. 2009. “On the Application of the MODTRAN4 Atmospheric Radiative Transfer Code to Optical Remote Sensing.” International Journal of Remote Sensing 30 (6): 1407–1424. https://doi.org/10.1080/01431160802438555.
  • Jiménez-Muñoz, J. C., J. A. Sobrino, C. Mattar, and B. Franch. 2010. “Atmospheric Correction of Optical Imagery from MODIS and Reanalysis Atmospheric Products.” Remote Sensing of Environment 114 (10): 2195–2210. https://doi.org/10.1016/j.rse.2010.04.022.
  • Kotchenova, S. Y., E. F. Vermote, R. Matarrese, and F. J. Klemm Jr. 2006. “Validation of a Vector Version of the 6S Radiative Transfer Code for Atmospheric Correction of Satellite Data. Part I: Path Radiance.” Applied Optics 45 (26): 6762–6774. https://doi.org/10.1364/AO.45.006762.
  • Krizhevsky, A., I. Sutskever, and G. E. Hinton. 2017. “Imagenet Classification with Deep Convolutional Neural Networks.” Communications of the ACM 60 (6): 84–90. https://doi.org/10.1145/3065386.
  • Lee, K.-S., E. Lee, D. Jin, N.-H. Seong, D. Jung, S. Sim, and K.-S. Han. 2022. “Retrieval and Uncertainty Analysis of Land Surface Reflectance Using a Geostationary Ocean Color Imager.” Remote Sensing 14 (2): 360. https://doi.org/10.3390/rs14020360.
  • Lee, C. S., J. Min Yeom, H. Lim Lee, J.-J. Kim, and K.-S. Han. 2015. “Sensitivity Analysis of 6S-Based Look-Up Table for Surface Reflectance Retrieval.” Asia-Pacific Journal of Atmospheric Sciences 51 (1): 91–101. https://doi.org/10.1007/s13143-015-0062-9.
  • Lee, K.-S., C. Suk 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.
  • Liang, S., H. Fang, and M. Chen. 2001. “Atmospheric Correction of Landsat ETM+ Land Surface Imagery. I. Methods.” IEEE Transactions on Geoscience and Remote Sensing 39 (11): 2490–2498. https://doi.org/10.1109/36.964986.
  • Liang, S., D. Wang, and T. He. 2010. “GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Surface Albedo.” NOAA NESDIS Center for Satellite Applications and Research, Version 1.0.
  • Liang, S., D. Wang, Y. Zhou, Y. Yu, and J. Peng. 2018. “VIIRS NDE Surface Albedo Algorithm Theoretical Basis Document.” NOAA, Version 1 (3). Accessed May 10, 2023. https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_EPS_Land_SurfaceAlbedo_v1.3.pdf.
  • Lyapustin, A., J. Martonchik, Y. Wang, I. Laszlo, and S. Korkin. 2011. “Multiangle Implementation of Atmospheric Correction (MAIAC): 1. Radiative Transfer Basis and Look-Up Tables.” Journal of Geophysical Research Atmospheres 116 (D3). https://doi.org/10.1029/2010JD014985.
  • Ma, R., H. Letu, K. Yang, T. Wang, C. Shi, J. Xu, J. Shi, C. Shi, and L. Chen. 2020. “Estimation of Surface Shortwave Radiation from Himawari-8 Satellite Data Based on a Combination of Radiative Transfer and Deep Neural Network.” IEEE Transactions on Geoscience & Remote Sensing 58 (8): 5304–5316. https://doi.org/10.1109/TGRS.2019.2963262.
  • Pacifici, F., N. Longbotham, and W. J. Emery. 2014. “The Importance of Physical Quantities for the Analysis of Multitemporal and Multiangular Optical Very High Spatial Resolution Images.” IEEE Transactions on Geoscience and Remote Sensing 52 (10): 6241–6256. https://doi.org/10.1109/TGRS.2013.2295819.
  • PlanetLabs. 2023. “Planet Surface Reflectance Version 2.0.” Accessed May 15, 2023. https://assets.planet.com/marketing/PDF/Planet_Surface_Reflectance_Technical_White_Paper.pdf.
  • Qu, Y., Q. Liu, S. Liang, L. Wang, N. Liu, and S. Liu. 2013. “Direct-Estimation Algorithm for Mapping Daily Land-Surface Broadband Albedo from MODIS Data.” IEEE Transactions on Geoscience and Remote Sensing 52 (2): 907–919. https://doi.org/10.1109/TGRS.2013.2245670.
  • Rabah, M., and M. Kaloop. 2013. “The Use of Minimum Curvature Surface Technique in Geoid Computation Processing of Egypt.” Arabian Journal of Geosciences 6 (4): 1263–1272. https://doi.org/10.1007/s12517-011-0418-0.
  • Roger, J. C., E. F. Vermote, and J. P. Ray. 2015. “MODIS surface reflectance user’s guide.” MODIS Land Surface Reflectance Science Computing Facility, Version 1.4.
  • SIIS. 2023. Accessed May 12, 2023. https://www.si-imaging.com/.
  • Thomas, J., S. Thomas, and L. Sael. 2017. “Feature versus Raw Sequence: Deep Learning Comparative Study on Predicting Pre-MiRNA.” arXiv E-Prints arXiv–1710.
  • Vermote, E., C. Justice, M. Claverie, and B. Franch. 2016. “Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product.” Remote Sensing of Environment 185:46–56. https://doi.org/10.1016/j.rse.2016.04.008.
  • Vermote, E. F., and S. Kotchenova. 2008. “Atmospheric Correction for the Monitoring of Land Surfaces.” Journal of Geophysical Research: Atmospheres113 (D23). https://doi.org/10.1029/2007JD009662.
  • Vermote, E. F. T. D., D. Tanré, J. L. Deuzé, M. Herman, J. J. Morcrette, and S. Y. Kotchenova. 2006. “Second Simulation of a Satellite Signal in the Solar Spectrum-Vector (6SV).” 6S User Guide Version 3 (2): 1–55.
  • Yeom, J.-M., S. Park, T. Chae, J.-Y. Kim, and C. Suk Lee. 2019. “Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Using Data Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea.” Sensors 19 (9): 2082. https://doi.org/10.3390/s19092082.
  • Yuan, Q., H. Shen, T. Li, Z. Li, S. Li, Y. Jiang, H. Xu, et al. 2020. “Deep Learning in Environmental Remote Sensing: Achievements and Challenges.” Remote Sensing of Environment 241:111716. https://doi.org/10.1016/j.rse.2020.111716.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.