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Day-1 INSAT-3DR Vicarious Calibration Using Reflectance-Based Approach Over Great Rann of Kutch

  • Piyushkumar N. Patel
  • K. N. Babu
  • R. P. Prajapati
  • Vikram Sitapara
  • A. K. Mathur
Research Article
  • 48 Downloads

Abstract

This study describes the post-launch calibration for visible (VIS) and shortwave infrared (SWIR) bands of Indian National Satellite System (INSAT)-3DR imager over Great Rann of Kutch (GROK) on Day-1 (15th September 2016), when the first time INSAT-3DR Imager camera was switched on. In order to account the characterization of errors and undetermined post-launch changes in sensor spectral response, this calibration activity was performed and extended for its monitoring to Day-56 (since the Day-1; 09th November 2016). A reflectance based technique is used in the present study. The surface reflectance and atmospheric variables were measured over the site as per solar and viewing geometry of the INSAT-3D scan. Top of atmosphere (TOA) spectral radiances were computed using 6SV (second simulation of the satellite signal in the solar spectrum) radiative transfer code with the in situ measurements as well as spectral response function of each channel. Preliminary results of the Day-1 vicarious calibration yield gain coefficients of 0.974 and 0.820 for VIS and SWIR channels respectively despite the inhomogeneity of the ground target caused by sufficient sub-surface soil moisture. In extension of the present study, the obtained gain coefficients were 1.001 and 0.9887 for VIS and SWIR, respectively, during Day-56 which indicates the performance of sensor is within the range of pre-launch laboratory calibration.

Keywords

INSAT-3DR Vicarious calibration Reflectance 6SV Radiative transfer model 

Notes

Acknowledgements

The authors gratefully acknowledge the encouragement received from Tapan Misra, Director, SAC for carrying out the present research work. Valuable suggestions received from Dr Raj Kumar, Deputy Director, EPSA is also gratefully acknowledged. Authors would like to thanks their respective families for their continuous motivations. The authors are grateful to anonymous reviewers for constructive and useful comments.

References

  1. Badarinath, K. V. S., Kharol, S. K., Kaskaoutis, D. G., & Kambezidis, H. D. (2007). Dust storm over indian region and its impact on the ground reaching solar radiation—A case study using multi-satellite data and ground measurements. Science of the Total Environment, 384, 316–332.CrossRefGoogle Scholar
  2. Bannari, A., Omari, K., Teillet, P. M., & Fedosejevs, G. (2005). Potential of Getis statistics to characterize the radiometric uniformity and stability of test sites used for the calibration of Earth observation sensors. IEEE Transactions on Geoscience and Remote Sensing, 43(12), 2918–2926.CrossRefGoogle Scholar
  3. Bouvet, M. (2014). Radiometric comparison of multispectral imagers over a pseudo-invariant calibration site using a reference radiometric model. Remote Sensing of Environment, 140, 141–154.CrossRefGoogle Scholar
  4. Bruegge, C. J., Duval, V. G., Chrien, N. L., Korechoff, R. P., Gaitley, B. J., & Hochberg, E. B. (1998). MISR prelaunch instrument calibration and characterization results. IEEE Transactions on Geoscience and Remote Sensing, 36, 1186–1198.CrossRefGoogle Scholar
  5. Bruegge, C. J., Stiegman, A. E., Rainen, R. A., & Springsteen, A. W. (1993). Use of Spectralon as a diffuse reflectance standard for in-flight calibration of earth-orbiting sensors. Optical Engineering, 32, 805–814.CrossRefGoogle Scholar
  6. Chander, G., Xiong, X., Choi, T., & Angal, A. (2010). Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites. Remote Sensing of Environment, 114, 925–939.CrossRefGoogle Scholar
  7. Chen, Z., Zhang, B., Zhang, H., & Zhang, W. (2014). Vicarious calibration of Beijing-1 multispectral imagers. Remote Sensing, 6, 1432–1450.  https://doi.org/10.3390/rs6021432.CrossRefGoogle Scholar
  8. Cosnefroy, H., Leroy, M., & Briottet, X. (1996). Selection and characterization of Saharan and Arabian desert sites for the calibration of optical satellite sensors. Remote Sensing of Environment, 58, 101–114.CrossRefGoogle Scholar
  9. Czapla-Myres, J., McCorkel, J., Anderson, N., Thome, K., Biggar, S., Helder, D., et al. (2015). The ground-based absolute radiometric calibration of landsat 8 OLI. Remote Sensing, 7, 600–626.  https://doi.org/10.3390/rs/0100600.CrossRefGoogle Scholar
  10. Frouin, R., & Gautier, C. (1987). Calibration of NOAA-7 AVHRR, GOES-5, and GOES-6 VISSR/VAS solar channels. Remote Sensing of Environment, 22, 73–101.CrossRefGoogle Scholar
  11. Gellman, D. I., Biggar, S. F., Slater, P. N., & Bruegge, C. J. (1991). Calibrated intercepts for solar radiometers used in remote sensor calibration. Proceedings of SPIE, 1493, 19–24.Google Scholar
  12. Gu, X., Guyot, G., & Verbrugghe, M. (1990). Analyze de la variabilité spatiale d’un site-test: Exemple de “La Crau” (France). Photo Interpretation, 1(5), 39–52.Google Scholar
  13. Kotchenova, S. Y., Vermote, E. F., Levy, R., & Lyapustin, A. (2008). Radiative transfer codes for atmospheric correction and aerosol retrieval: Intercomparison study. Applied Optics, 47(13), 2215–2226.CrossRefGoogle Scholar
  14. Markham, B. L., Halthore, R. N., & Goetz, S. J. (1992). Surface reflectance retrieval from satellite and aircraft sensors: results of sensor and algorithm comparison during FIFE. Journal of Geophysical Research, 97(D17), 18785–18795.  https://doi.org/10.1029/92JD02077.CrossRefGoogle Scholar
  15. MODIS ATBD, Strahler, A. H., & Muller, J. P. (1999). MODIS BRDF/Albedo Product, Algorithm Theoretical Basis Document, Version 6.Google Scholar
  16. Morys, M., Mims, F. M., III, Hagerup, S., Anderson, S. E., Baker, A., Kia, J., et al. (2001). Design, calibration, and performance of MICROTOPS II handheld ozone monitor and Sun photometer. Journal of Geophysical Research, 106(D13), 14573–14582.CrossRefGoogle Scholar
  17. Nicodemus, F. E., Richmond, J. C., Hsia, J. J., Ginsberg, I. W., & Limperis, T. (1977). Geometrical considerations and nomenclature for reflectance, Natl. Bur. Stand. Rep. NBS MN-160, 52.Google Scholar
  18. Patel, P., Bhatt, H., & Shukla, A. K. (2014). Absolute vicarious calibration of recently launched Indian meteorological satellite: INSAT-3D imager. ISPRS technical Commission VIII symposium, 09–12 December, 2014, Hyderabad, India.  https://doi.org/10.5194/isprsarchives-XL-8-291-2014.
  19. Patel, P., Bhatt, H., Mathur, A. K., Prajapati, R. P., & Tyagi, G. (2016). Reflectance-based vicarious calibration of INSAT-3D using high-reflectance ground target. Remote Sensing Applications: Society and Environment, 3, 20–35.  https://doi.org/10.1016/j.rsase.2015.12.001.CrossRefGoogle Scholar
  20. Porter, J. N., Miller, M., Pietras, C., & Motell, C. (2001). Ship-based sun photometer measurements using microtops sun photo-meters. Journal of Atmospheric and Oceanic Technology, 18, 765–774.CrossRefGoogle Scholar
  21. Rao, C. R. N. (2001). Implementation of the post-launch vicarious calibration of the GOES imager visible channel (Camp Springs, MD: NOAA Satellite and Information Services (NOAA/NESDIS)). http://www.ospo.noaa.gov/Operations/GOES/calibration/vicarious-calibration.html.
  22. Reagan, J. A., Thomason, L. W., Herman, B. M., & Palmer, J. M. (1986). Assessment of atmospheric limitations on the determination of the solar spectral constant from ground-based spectroradiometer measurements. IEEE Transactions on Geoscience and Remote Sensing., 24, 258–266.CrossRefGoogle Scholar
  23. Rondeaux, G., Steven, M. D., Clark, J. A., & Mackay, G. (1998). La Crau: A European test site for remote sensing validation. International Journal of Remote Sensing, 19(14), 2775–2788.CrossRefGoogle Scholar
  24. Schmid, B., & Wehrli, C. (1995). Comparison of sun photometer calibration by use of the Langley technique and standard lamp. Applied Optics, 34, 4500–4512.CrossRefGoogle Scholar
  25. Scott, K. P., Thome, K. J., & Brownlee, M. (1996). Evaluation of the railroad valley playa for use in vicarious calibration. Proceedings SPIE, 2818, 158–166.CrossRefGoogle Scholar
  26. Slater, P. N., Biggar, S. F., Holm, R. A., Jackson, R. D., Mao, Y., Moran, M. S., et al. (1987). Reflectance-and radiance-based methods for in-flight absolute calibration of multispectral sensors. Remote Sensing of Environment, 22(11–37), 1987.Google Scholar
  27. Slater, P. N., Biggar, S. F., Thome, K. J., Gellman, D. I., & Spyak, P. R. (1996). Vicarious radiometric calibrations of EOS sensors. Journal of Atmospheric and Oceanic Technology, 13, 349–359.CrossRefGoogle Scholar
  28. Teillet, P., & Chander, G. (2010). Terrestrial reference standard sites for post-launch sensor calibration. Canadian Journal of Remote Sensing, 36, 437–450.CrossRefGoogle Scholar
  29. Teillet, P. M., Horler, D., & O’Neill, N. T. (1997). Calibration, validation, and quality assurance in remote sensing: A new paradigm. Canadian Journal of Remote Sensing, 23(4), 401–414.CrossRefGoogle Scholar
  30. Thome, K. J. (2001). Absolute radiometric calibration of Landsat 7 ETM+ using the reflectance-based method. Remote Sensing of Environment, 78, 27–38.CrossRefGoogle Scholar
  31. Thome, K., Schiller, K. S., Conel, J., Arai, K., & Tsuchida, S. (1998). Results of the 1997 Earth Observing System Vicarious Calibration joint campaign at Lunar Lake Playa, Nevada (USA). Metrologia, 35, 631–638.CrossRefGoogle Scholar
  32. Vermote, E. D., Tanre, J. L., Deuze, M., Herman, J. J., Morcrette, & Kotchenova, S. Y. (2006). Second simulation of satellite signal in the satellite spectrum (6S). 6S User Guide Version 3. University of Maryland.Google Scholar

Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  • Piyushkumar N. Patel
    • 1
  • K. N. Babu
    • 1
  • R. P. Prajapati
    • 1
  • Vikram Sitapara
    • 1
  • A. K. Mathur
    • 1
  1. 1.Calibration and Validation Division, Space Applications CentreISROAhmedabadIndia

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