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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 20, Iss. 16 — Jul. 30, 2012
  • pp: 17760–17766

Validation of MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared channel with field measurements

Bo-Hui Tang, Hua- Wu, Zhao-Liang Li, and Françoise Nerry  »View Author Affiliations


Optics Express, Vol. 20, Issue 16, pp. 17760-17766 (2012)
http://dx.doi.org/10.1364/OE.20.017760


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Abstract

This work addressed the validation of the MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared (MIR) channel, proposed by Tang and Li [Int. J. Remote Sens. 29, 4907 (2008)], with ground-measured data, which were collected from a field campaign that took place in June 2004 at the ONERA (Office National d’Etudes et de Recherches Aérospatiales) center of Fauga-Mauzac, on the PIRRENE (Programme Interdisciplinaire de Recherche sur la Radiométrie en Environnement Extérieur) experiment site [Opt. Express 15, 12464 (2007)]. The leaving-surface spectral radiances measured by a BOMEM (MR250 Series) Fourier transform interferometer were used to calculate the ground brightness temperatures with the combination of the inversion of the Planck function and the spectral response functions of MODIS channels 22 and 23, and then to estimate the ground brightness temperature without the contribution of the solar direct beam and the bidirectional reflectivity by using Tang and Li’s proposed algorithm. On the other hand, the simultaneously measured atmospheric profiles were used to obtain the atmospheric parameters and then to calculate the ground brightness temperature without the contribution of the solar direct beam, based on the atmospheric radiative transfer equation in the MIR region. Comparison of those two kinds of brightness temperature obtained by two different methods indicated that the Root Mean Square Error (RMSE) between the brightness temperatures estimated respectively using Tang and Li’s algorithm and the atmospheric radiative transfer equation is 1.94 K. In addition, comparison of the hemispherical-directional reflectances derived by Tang and Li’s algorithm with those obtained from the field measurements showed that the RMSE is 0.011, which indicates that Tang and Li’s algorithm is feasible to retrieve the bidirectional reflectivity in MIR channel from MODIS data.

© 2012 OSA

OCIS Codes
(070.4790) Fourier optics and signal processing : Spectrum analysis
(120.0120) Instrumentation, measurement, and metrology : Instrumentation, measurement, and metrology
(280.0280) Remote sensing and sensors : Remote sensing and sensors
(350.6980) Other areas of optics : Transforms
(280.4991) Remote sensing and sensors : Passive remote sensing
(290.6815) Scattering : Thermal emission

ToC Category:
Remote Sensing

History
Original Manuscript: June 18, 2012
Revised Manuscript: July 13, 2012
Manuscript Accepted: July 15, 2012
Published: July 19, 2012

Citation
Bo-Hui Tang, Hua- Wu, Zhao-Liang Li, and Françoise Nerry, "Validation of MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared channel with field measurements," Opt. Express 20, 17760-17766 (2012)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-20-16-17760


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References

  1. Y. J. Kaufman and L. A. Remer, “Detection of forests using MID-IR reflectance: an application for aerosol studies,” IEEE Trans. Geosci. Rem. Sens.32(3), 672–683 (1994). [CrossRef]
  2. W. C. Snyder, Z. Wan, Y. Zhang, and Y. Feng, “Thermal infrared (3-14 μm) bi-directional reflectance measurement of sands and soils,” Remote Sens. Environ.60(1), 101–109 (1997). [CrossRef]
  3. D. S. Boyd, G. M. Foody, and P. J. Curran, “The relationship between the biomass of Cameroonian tropical forests and radiation reflected in middle infrared wavelengths (3.0-5.0 μm),” Int. J. Remote Sens.20(5), 1017–1023 (1999). [CrossRef]
  4. D. S. Boyd and F. Petitcolin, “Remote sensing of the terrestrial environment using middle infrared radiation (3.0-5.0 μm),” Int. J. Remote Sens.25(17), 3343–3368 (2004). [CrossRef]
  5. R. Libonati, C. C. DaCamara, J. M. C. Pereira, and L. F. Peres, “Retrieving middle-infrared reflectance for burned area mapping in tropical environments using MODIS,” Remote Sens. Environ.114(4), 831–843 (2010). [CrossRef]
  6. Z.-L. Li and F. Becker, “Feasibility of land surface temperature and emissivity determination from NOAA/AVHRR data,” Remote Sens. Environ.43(1), 67–86 (1993). [CrossRef]
  7. F. Nerry, F. Petitcolin, and M. P. Stoll, “Bidirectional reflectivity in AVHRR channel 3: application to a region in northern Africa,” Remote Sens. Environ.66(3), 298–316 (1998). [CrossRef]
  8. Z.-L. Li, F. Petitcolin, and R. H. Zhang, “A physically based algorithm for land surface emissivity retrieval from combined mid-infrared and thermal infrared data,” Sci. China Ser. E: Technol. Sci.43(S1Supp), 23–33 (2000). [CrossRef]
  9. B.-H. Tang and Z.-L. Li, “Retrieval of land surface bidirectional reflectivity in the mid-infrared from MODIS channel 22 and 23,” Int. J. Remote Sens.29(17-18), 4907–4925 (2008). [CrossRef]
  10. K. Kanani, L. Poutier, F. Nerry, and M. P. Stoll, “Directional effects consideration to improve out-doors emissivity retrieval in the 3-13 mum domain,” Opt. Express15(19), 12464–12482 (2007). [CrossRef] [PubMed]
  11. Z.-L. Li, B. Tang, and Y. Bi, “Estimation of land surface directional emissivity in mid-infrared channel around 4.0 µm from MODIS data,” Opt. Express17(5), 3173–3182 (2009). [CrossRef] [PubMed]

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