Journal of the Korean Society for Aeronautical & Space Sciences (한국항공우주학회지)

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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A Study on Possibility of Improvement of MIR Brightness Temperature Bias Error of KOMPSAT-3A Using GEOKOMPSAT-2A

천리안2A호를 이용한 다목적실용위성3A호 중적외선 밝기 온도 편향오차 개선 가능성 연구

  • Received : 2020.08.21
  • Accepted : 2020.10.20
  • Published : 2020.12.01
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Abstract

KOMPSAT-3A launched in 2015 provides Middle InfraRed(MIR) images with 3.3~5.2㎛. Though the satellite provide high resolution images for estimating bright temperature of ground objects, it is different from existing satellites developed for natural science purposes. An atmospheric compensation process is essential in order to estimate the surface brightness temperature from a single channel MIR image of KOMPSAT-3A. However, even after the atmospheric compensation process, there is a brightness temperature error due to various factors. In this paper, we analyzed the cause of the brightness temperature estimation error by tracking signal flow from camera physical characteristics to image processing. Also, we study on possibility of improvement of MIR brightness temperature bias error of KOMPSAT-3A using GEOKOMPSAT-2A. After bias compensation of a real nighttime image with a large bias error, it was confirmed that the surface brightness temperature of KOMPSAT-3A and GEOKOMPSAT-2A have correlation. We expect that the GEOKOMPSAT-2A images will be helpful to improve MIR brightness temperature bias error of KOMPSAT-3A.

2015년 발사된 다목적실용위성 3A호는 3.3~5.2㎛ 파장의 중적외선 영상을 제공한다. 다목적실용위성 3A호는 지상 물체의 밝기 온도를 추정하기 위한 고해상도 영상을 제공하지만 기존 자연 과학 목적으로 개발된 위성과 차이가 있다. 다목적실용위성 3A호의 단일 채널의 중적외선 영상으로 지표 밝기 온도를 추정하기 위해서는 대기 보정 과정이 필수적이다. 하지만 대기 보정 이후에도 여러 요인으로 인하여 밝기 온도 추정 오차가 존재한다. 본 논문에서는 다목적실용위성 3A호 카메라의 물리적인 특성으로부터 영상 처리까지 신호 흐름을 추적하여 밝기 온도 추정 오차 요인을 분석하였다. 또한, 천리안위성 2A호를 이용하여 다목적실용위성 3A호와 밝기 온도 편향 오차 개선 가능성을 연구하였다. 큰 편향 오차를 가지고 있는 야간 영상에 대하여 편향 오차를 보상한 이후 다목적실용위성 3A호와 천리안위성 2A호의 지표 밝기 온도가 상관성이 있음을 확인하였다. 다목적실용위성 3A호 중적외선 밝기 온도 편향 오차를 개선하는데 천리안위성 2A호 영상이 도움이 될 것으로 예상된다.

Keywords

References

  1. Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F. and Sobrino, J. A., "Satellite-derived land surface temperature: Current status and perspectives," Remote Sensing of Environment, Vol. 131, 2013, pp. 14-37. https://doi.org/10.1016/j.rse.2012.12.008
  2. Petitcolin, F. and Vermote, E., "Land surface reflectance, emissivity and temperature from MODIS middle and thermal infrared data," Remote Sensing of Environment, Vol. 83, 2002, pp. 112-134. https://doi.org/10.1016/S0034-4257(02)00094-9
  3. Park, S. H., Jung, H. S. and Shin, H. S., "An efficient Method to Estimate Land Surface Temperature Difference (LSTD) Using Landsat Satellite Images," Korean Journal of Remote Sensing, Vol. 29, No. 2, 2013, pp. 197-207. https://doi.org/10.7780/kjrs.2013.29.2.4
  4. Yu, X., Guo, X. and Wu, Z., "Land Surface Temperature Retrieval from Landsat 8 TIRS-Comparison between Radiative Transfer Equation-Base Method, Split Window Algorithm and Single Channel Method," Remote Sensing, 2014, Vol. 6, pp. 9829-9852. https://doi.org/10.3390/rs6109829
  5. Gillespie, A. M., Rokugawa, S., Matsunaga, T., Cothern, J. S., Hook, S. and Kahle, A. B., "A Temperature and Emissivity Separation Algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Images," IEEE Transactions on Geoscience and Remote Sensing, 1998, Vol. 36, No. 4, pp. 1113-1125. https://doi.org/10.1109/36.700995
  6. Petitcolin, F. and Vermote, E., "Land surface reflectance, emissivity and temperature from MODIS middle and thermal infrared data," Remote Sensing of Environment, 2002, Vol. 83, pp. 112-134. https://doi.org/10.1016/S0034-4257(02)00094-9
  7. Berk, A., Anderson, G. P., Acharya, P. K. and Shettle, E. P., "MODTRAN 5.2.0.0 User"s Manual," Air force research laboratory, 2008.
  8. Choi, Y. Y. and Suh, M. S., "Development of a Land Surface Temperature Retrieval Algorithm from KG2A/AMI," Remote Sensing, 2020, Vol. 12, No. 18, 3050. https://doi.org/10.3390/rs12183050
  9. Barsi, J. A., Schott, J. R., Hook, S. J., Raqueno, N. G., Markham, B. L. and Radocinski, R. G., "Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration," Remote Sensing, 2014, Vol. 6, No. 11, pp. 11607-11626. https://doi.org/10.3390/rs61111607
  10. Cook, M., Schott, J. R., Mandel, J. and Raqueno, N., "Development of an Operational Calibration Methodology for the Landsat Thermal Data Archive and Initial Testing of the Atmospheric Compensation Component of a Land Surface Temperature (LST) Product from the Archive," Remote Sensing, 2014, Vol. 6, No. 11, pp. 11244-11266. https://doi.org/10.3390/rs61111244
  11. Kim, H. S., Chung, D. W. and Kim G. S., "Method of Generating Satellite Simulated Image in the Point of MTF," Aerospace Engineering and Technology, 2007, Vol. 6, No. 1, pp. 97-1023.
  12. Griffin, M. K., Burke, H. K. and Kerekes, J. P., "Understanding radiative transfer in the midwave infrared: A precursor to full spectrum atmospheric compensation," In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, International Society for Optics and Photonics, 2004, Vol. 5425, pp. 348-356.
  13. Won, J. S., "A Study of Absolute and Relative Temperature Retrieval from Space-borne High Resolution Mid-wavelength Infrared(MWIR) Images," Research Report of Korea Aerospace Research Institute, 2019.
  14. Baldridge, A. M., Hook, S. J., Grove, C. I. and Rivera, G., The Aster Spectral Library Version 2.0, Remote Sensing of Environment, 2009, Vol. 113, pp. 711-715. https://doi.org/10.1016/j.rse.2008.11.007