DOI QR코드

DOI QR Code

Absolute Radiometric Calibration for KOMPSAT-3 AEISS and Cross Calibration Using Landsat-8 OLI

  • Ahn, Hoyong (Dept. of Spatial Information Engineering, Pukyoung National University) ;
  • Shin, Dongyoon (Road Policy Research Center, Korea Research Institute for Human Settlements) ;
  • Lee, Sungu (Ground System Development Team, Korea Aerospace Research Institute) ;
  • Choi, Chuluong (Dept. of Spatial Information Engineering, Pukyoung National University)
  • Received : 2017.07.31
  • Accepted : 2017.08.30
  • Published : 2017.08.31

Abstract

Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remotely sensed data. This paper presents absolute radiometric calibration of the KOMPSAT-3 (KOrea Multi Purpose SATellite-3) and cross calibration using the Landsat-8 OLI (Operational Land Imager). Absolute radiometric calibration was performed using a reflectance-based method. Correlations between TOA (Top Of Atmosphere) radiances and the spectral band responses of the KOMPSAT-3 sensors in Goheung, South Korea, were significant for multispectral bands. A cross calibration method based on the Landsat-8 OLI was also used to assess the two sensors using near simultaneous image pairs over the Libya-4 PICS (Pseudo Invariant Calibration Sites). The spectral profile of the target was obtained from EO-1 (Earth Observing-1) Hyperion data over the Libya-4 PICS to derive the SBAF (Spectral Band Adjustment Factor). The results revealed that the TOA radiance of the KOMPSAT-3 agree with Landsat-8 within 5.14% for all bands after applying the SBAF. The radiometric coefficient presented here appears to be a good standard for maintaining the optical quality of the KOMPSAT-3.

Keywords

References

  1. Amanollahi, J., Tzanis, C., Abdullah, A.M., Ramli, M.F., and Pirasteh, S. (2013), Development of the models to estimate particulate matter from thermal infrared band of Landsat Enhanced Thematic Mapper, International Journal of Environmental Science and Technology, Vol. 10, No. 6, pp. 1245-1254. https://doi.org/10.1007/s13762-012-0150-7
  2. Belward, A.S. and Valenzuela, C.R. (1991), Remote Sensing and Geographical Information System for Resource Management in Developing Countries, Kluwer Academic, Netherlands.
  3. Chander, G., Mishra, N., Helder, D.L., Aaron, D., Angal, A., Choi, T., Xiong, X., and Doelling, D. (2013), Applications of spectral band adjustment factors (SBAF) for cross calibration, IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, No. 3, pp. 1267-1281. https://doi.org/10.1109/TGRS.2012.2228007
  4. Chander, G., Mishra, N., Helder, D.L., Aaron, D., Choi, T., Angal, A., and Xiong, X. (2010), Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors, Proceedings of IEEE International Geoscience and Remote Sensing Symposium, IEEE, 25-30 July, Honolulu, Hawaii, pp. 1667-1670.
  5. Dinguirard, M. and Slater, P.N. (1999), Calibration of spacemultispectral imaging sensors: A review, Remote Sensing of Environment, Vol. 68, No. 3, pp. 194-205. https://doi.org/10.1016/S0034-4257(98)00111-4
  6. Folkman, M.A., Pearlman J., Liao B.L., and Jarecke P.J. (2001), EO-1/Hyperion hyperspectral imager design, development, characterization, and calibration, Proceedings of Hyperspectral Remote Sensing of the Land and Atmosphere, SPIE, 9-12 October, Sendai, Japan, pp. 40-51.
  7. Fontenla, J.M., Harder, J., Livingston, W., Snow, M., and Woods, T. (2011), High-resolution solar spectral irradiance from extreme ultraviolet to far infrared, Journal of Geophysical Reasearch: Atmospheres, Vol. 116, No. D20.
  8. Irons, J.R., Dwyer, J.L., and Barsi, J.A. (2012), The next Landsat satellite: The Landsat Data Continuity Mission, Remote Sensing of Environment, Vol. 122, pp. 11-21. https://doi.org/10.1016/j.rse.2011.08.026
  9. Jin, C.G. and Lee, S.G (2014), Cross calibration for KOMPSAT2 MSC images using EO-1 Hyperion, Proceedings of the International Symposium on Remote Sensing, ISRS, 16-18 April, Busan, Korea, unpaginated CD-ROM.
  10. Kim J.S., Jin, C.G., Choi, C.U., and Ahn. H.Y. (2015), Radiometric characterization and validation for the KOMPSAT-3 sensor, Remote Sensing Letters, Vol. 6, No. 7, pp. 529-538. https://doi.org/10.1080/2150704X.2015.1054043
  11. Lee, S.G., Jin, C.G., Choi, C.U., Lim, H.S., Kim, Y.S., and Kim, J.S. (2012), Absolute radiometric calibration of the KOMPSAT2 multispectral camera using a reflectancebased method and empirical comparison with IKONOS and QuickBird images, Journal of Applied Remote Sensing, Vol. 6, No. 1, pp. 063594-063594. https://doi.org/10.1117/1.JRS.6.063594
  12. Mishra, N., Haque, M.O., Leigh, L., Aaron, D., Helder, D.L., and Markham, B.L. (2014), Radiometric cross calibration of Landsat-8 Operational Land Imager (OLI) and Landsat7 Enhanced Thematic Mapper Plus (ETM+), Remote Sensing, Vol. 6, No. 12, pp. 12619-12638. https://doi.org/10.3390/rs61212619
  13. Morakot K., Chaichat, M., and Panatda K. (2013), The effect of extraterrestrial solar model and spectral differences on cross calibration, Proceedings of the 34th Asian Conference on Remote Sensing, 20-24 October, Bali, Indonesia, unpaginated CD-ROM.
  14. Pagnutti, M., Ryan, R.E., Kelly, M., Holekamp, K., Zanoni, V., Thome, K., and Schiller, S. (2003), Radiometric characterization of IKONOS multispectral imagery, Remote Sensing of Environment, Vol. 88, No. 1, pp. 53-68. https://doi.org/10.1016/j.rse.2003.07.008
  15. Richter, R. and Schläpfer, D. (2011), Atmospheric/ Topographic Correction for Satellite Imagery, DLR Report, German Aerospace Center, D-82234, Wessling, Germany, DLR-IB 565-02/11.
  16. Schlapfer, D. and Nieke, J. (2005), Operational simulation of at sensor radiance sensitivity using the MODO/ MODTRAN4 environment, Proceedings of the 4th EARSeL Workshop on Imaging Spectroscopy, 27-30 April, Warsaw, Poland, pp. 611-619.
  17. Teillet, P.M., Barker, J.L., Markham, B.L., Irish, R.R., Fedosejevs, G., and Storey, J.C. (2001), Radiometric crosscalibration of the Landsat-7 ETM+ and Landsat-5 TM sensors based on tandem data sets, Remote Sensing of Environment, Vol. 78, No. 1, pp. 39-54. https://doi.org/10.1016/S0034-4257(01)00248-6
  18. Teillet, P.M., Fedosejevs, G., Gauthier, R., O'Neill, N., Thome, K.J., Biggar, S.F., Ripley, H., and Meygret, A. (2001), A generalized approach to the vicarious calibration of multiple Earth observation sensors using hyperspectral data, Remote Sensing of Environment, Vol. 77, No. 3, pp. 304-327. https://doi.org/10.1016/S0034-4257(01)00211-5
  19. Teillet, P.M., Slater, P.N., Ding, Y., Santer, R.P., Jackson, R.D., and Moran, M.S. (1990), Three methods for the absolute calibration of the NOAA AVHRR sensors inflight, Remote Sensing of Environment, Vol. 31, No. 2, pp. 105-120. https://doi.org/10.1016/0034-4257(90)90060-Y
  20. Thome, K.J. (2001), Absolute radiometric calibration of Landsat7 ETM+ using the reflectance-based method, Remote Sensing of Environment, Vol. 78, No. 1, pp. 27-38. https://doi.org/10.1016/S0034-4257(01)00247-4
  21. Ungar, S., Middleton, E., Ong, L., and Campbell, P. (2009), EO-1 Hyperion onboard performance over eight years: Hyperion calibration, Proceedings of 6th European Association of Remote Sensing Laboratories, EARSeL, 16-19 March, Tel Aviv, Israel, pp. 1-6.
  22. Yang, X.J. and Lo, C.P. (2000), Relative radiometric normalization performance for change detection from multi-date satellite images, Photogrammetric Engineering and Remote Sensing, Vol. 66, No. 8, pp. 967-980.