Abstract
We created a look-up table (LUT) based on the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model, which reduces large errors in the surface reflectance retrieval under high solar zenith angle (SZA) conditions. The LUT was calculated in 10° SZA intervals containing pre-computed atmospheric correction coefficients as a function of discretized pre-defined input parameters. In order to validate the performance of the LUT, we compared the retrieved surface reflectance using the LUT against a retrieval performed using the simplified method of atmospheric correction (SMAC). These results were validated against MODIS reflectance data (MOD09). The surface reflectance obtained using the LUT was highly correlated with the MOD09, with a coefficient of determination (R2) of 0.88 (red band) and 0.94 (NIR). The retrieved surface reflectance had a root mean-squared error of 0.0132 (red band) and 0.0191 (NIR). Accuracy of surface reflectance retrieved using our LUT with a 10° SZA interval was better than that of the obtained using SMAC. However, certain errors were still present particularly at high SZAs. In order to increase the accuracy at high SZAs, new LUT was computed with a finer SZA interval (5°) at high SZAs. In both red and NIR bands, the R2, fine SZA interval LUT (0.92) were compared to the coarse SZA interval LUT (0.74) of around 65°. Additionally, the run time for surface reflectance retrievals with our LUT was almost comparable to that of the SMAC, an operational model. This study demonstrates that proper SZAs interval for making LUT in high SZA range.
Similar content being viewed by others
References
Chen, P.-Y., R. Srinivasan, G. Fedosejevs, and J. R. Kiniry, 2003: Evaluation different NDVI composite techniques using NOAA-14 AVHRR data. Int. J. Remote Sens., 24, 3403–3412, doi: 10.1080/0143116021000021279.
Du, Y., P. M. Teillet, and J. Cihlar, 2002: Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection. Remote Sens. Environ., 82: 123–134, doi: 10.1016/S0034-4257(02)00029-9.
D’Almeida, G. A., P. Koepke, and E. P. Shettle, 1991: Atmospheric aerosols: global climatology and radiative characteristics. Hampton: A. Deepak Pub.
Fraser, R. S., R. A. Ferrare, Y. J. Kaufman, B. L. Markham, and S. Mattoo, 1992: Algorithm for atmospheric corrections of aircraft and satellite imagery. Int. J. Remote Sens., 13, 541–557, doi: 10.1080/014311692-08904056.
Gao, B. C., M. J. Montes, Z. Ahmad, and C. O. Davis, 2000: Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space. Appl. Optics, 39, 887–896, doi: 10.1364/AO.39.000887.
Hadjimitsis, D. G., C. R. I. Clayton, and V. S. Hope, 2004: An assessment of the effectiveness of atmospheric correction algorithms through the remote sensing of some reservoirs. Int. J. Remote Sens., 20, 3651–3674, doi: 10.1080/01431160310001647993.
Kotchenova, S. Y., and E. F. Vermote, 2007: Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part 2: Homogeneous Lambertian and anisotropic surfaces. Appl. Optics, 46, 4455–4464, doi: 10.1364/AO.46.004455.
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 1: Path radiance. Appl. Optics, 45: 6762–6774, doi: 10.1364/AO.45.006762.
Liang, S., H. Fang, and M. Chen, 2001: Atmospheric Correction of Landsat ETM+ Land Surface Imagery — Part I: Methods. IEEE Trans. Geosci. Remote Sens., 39, 2490–2498, doi: 10.1109/36.964986.
Liang, S., H. Fang, M. Chen, C. J. Shuey, C. Walthall, C. Daughtry, J. Morisette, C. Schaaf, and A. Strahler, 2002: Validating MODIS land surface reflectance and albedo products: methods and preliminary results. Remote Sens. Environ., 83, 149–162, doi: 10.1016/S0034-4257(02)00092-5.
Lu, D., P. Mausel, E. Brondizio, and E. Moran, 2002: Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int. J. Remote Sens., 23, 2651–2671, doi: 10.1080/01431160110109642.
Lyapustin, A., John Martonchik, Yujie Wang, Istvan Laszlo, and Sergey Korkin, 2011: Multiangle implementation of atmospheric correction (MAIAC): 1. Radiative transfer basis and look-up tables. J. Geophys. Res., 116, D03210, doi: 10.1029/2010JD014985.
Nunes, A. S. L., A. R. S. Marcal, and R. A. Vaughan, 2008: Fast over-land atmospheric correction of visible and near-infrared satellite image. Int. J. Remote Sens., 12, 3523–3531, doi: 10.1080/01431160701592445.
Proud, S. R., R. Fensholt, M. O. Rasmussen, and I. Sandholt, 2010a: A comparison of the effectiveness of 6S and SMAC in correcting for atmospheric interference of Meteosat Second Generation images. J. Geophys. Res., 115, D17209, doi: 10.1029/2009JD013693.
Proud, S. R., M. O. Rasmussen, R. Fensholt, I. Sandholt, C. Shisanya, W. Mutero, C. Mbow, and A. Anyamba, 2010b: Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data. Remote Sens. Environ., 114, 1687–1698, doi: 10.1016/j.rse.2010.02.020.
Rahman, H., and G. Dedieu, 1994: SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum. Int. J. Remote Sens., 15, 123–143, doi: 10.1080/01431169408954055.
Rautiainen, M., and P. Stenberg, 2005: Application of photon recollision probability in coniferous canopy reflectance simulations. Remote Sens. Environ., 96, 98–107, doi: 10.1016/j.rse.2005.02.009.
Sobrino, J. A., N. Raissouni, and Z.-L. Li, 2001: A comparative study of land surface emissivity retrieval from NOAA data. Remote Sens. Environ., 75, 256–266, doi: 10.1016/S0034-4257(00)00171-1.
Sobrino, J. A., J. C. Jimenez-Munoz, and L. Paolini, 2004: Land surface temperature retrieval from LANDSAT TM 5. Remote Sens. Environ., 90, 434–440, doi: 10.1016/j.rse.2004.02.003.
Tan, K. C., H. S. Lim, M. Z. Matjafri, and K. Adbullah, 2012: A comparison of radiometric correction techniques in the evaluation between LST and NDVI in Landsat imagery. Environ. Monit. Assess., 184, 3813–3829, doi: 10.1007/s10661-011-2226-0.
Thome, K. J., B. Markham, J. Barker, P. Slater, and S. Biggar, 1997: Radiometric Calibration of Landsat. Photogramm. Eng. Rem. S., 63, 835–858.
Yoo, J. M., M. J. Jeong, Y. M. Hur, and D. B. Shin, 2010: Improved fog detection from satellite in the presence of clouds. Asia-Pac. J. Atmos. Sci., 46: 29–40.
Vermote, E. F., and A. Vermeulen, 1999: Atmospheric Correction Algorithm: SPECTRAL REFLECTANCES (MOD09) version 4.0. Algorithm Technical Background Document (ATBD). http://modis.gsfc.nasa.gov/data/atbd/atbd_mod08.pdf.
Vermote, E. F., S. Y. Kotchenova, and J. P. Ray, 2011: MODIS Surface Reflectance User’s Guide. http://modis-sr.ltdri.org/products/MOD09_UserGuide_v1_3.pdf.
Vermote, E. F., and D. Tanre, J. L. Deuze, M. Herman, and J.-J. Morcrette, 1997: Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview. IEEE Trans. Geosci. Remote Sens., 35, 675–686, doi: 10.1109/36.581987.
Vermote, E. F., D. Tanre, J. J. Deuze, M. Herman, J. Morcrette, and S. Y. Kotchenove, 2006: Second Simulation of a Satellite Signal in the Solar Spectrum- Vector (6SV), 6S user guide, version 3. http://6s.ltdri.org/6S_code2_thiner_stuff/6s_ltdri_org_manual.htm.
Wang, M., 2003: An efficient method for multiple radiative transfer computations and the lookup table generation. J. Quant. Spectrosc. Ra., 78, 471–480, doi: 10.1016/S0022-4073(02)00278-9.
Xiao, X., B. Braswell, Q. Zhang, S. Boles, S. Frolking, and B. Moore III, 2003: Sensitivity of vegetation indices to atmospheric aerosols: continental-scale observations in Northern Asia. Remote Sens. Environ., 84, 385–392, doi: 10.1016/S0034-4257(02)00129-3.
Zhao, W., Masayuki Tamura, and T. Hidenori, 2000: Atmospheric and spectral corrections for estimating surface albedo from satellite data using 6S code. Remote Sens. Environ., 76, 202–212, doi: 10.1016/S0034-4257(00)00204-2.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lee, C.S., Yeom, J.M., Lee, H.L. et al. Sensitivity analysis of 6S-based look-up table for surface reflectance retrieval. Asia-Pacific J Atmos Sci 51, 91–101 (2015). https://doi.org/10.1007/s13143-015-0062-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13143-015-0062-9