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Analysis of Backscattering Coefficients of Corn Fields Using the First-Order Vector Radiative Transfer Technique

1차 Vector Radiative Transfer 기법을 이용한 옥수수 생육에 따른 후방산란 특성 분석

  • Kweon, Soon-Koo (Department of Electronic Information and Communication Engineering, Hongik University) ;
  • Hwang, Ji-Hwan (Department of Electronic Information and Communication Engineering, Hongik University) ;
  • Park, Sin-Myeong (Department of Electronic Information and Communication Engineering, Hongik University) ;
  • Hong, Sungwook (National Meteorological Satellite Center) ;
  • Oh, Yisok (Department of Electronic Information and Communication Engineering, Hongik University)
  • 권순구 (홍익대학교 전자정보통신공학과) ;
  • 황지환 (홍익대학교 전자정보통신공학과) ;
  • 박신명 (홍익대학교 전자정보통신공학과) ;
  • 홍성욱 (국가기상위성센터) ;
  • 오이석 (홍익대학교 전자정보통신공학과)
  • Received : 2013.12.04
  • Accepted : 2014.01.23
  • Published : 2014.04.30

Abstract

In this study, we analyzed the effect of corn growth on the radar backscattering coefficient. At first, we measured the backscattering coefficients of various corn fields using a polarimetric scatterometer system. The backscattering coefficients of the corn fields were also computed using the 1st-order VRT(Vector Radiative Transfer) model with field-measured input parameters. Then, we analyzed the experimental and numerical backscattering coefficients of corn fields. As a result, we found that the backscatter from an underlying soil layer is dominant for early growing stage. On the other hand, for vegetative stage with a higher LAI(Leaf-Area-Index), the backscatter from vegetation canopy becomes dominant, and its backscattering coefficients increase as incidence angle increases because of the effect of leaf angle distribution. It was also found that the estimated backscattering coefficients agree quite well with the field-measured radar backscattering coefficients with an RMSE(Root Mean Square Error) of 1.32 dB for VV-polarization and 0.99 dB for HH-polarization. Finally, we compared the backscattering characteristics of vegetation and soil layers with various LAI values.

본 연구에서는 위성 SAR 영상을 이용한 초목층 정보 예측을 위해 옥수수의 생육에 따른 후방 산란 계수 변화를 분석한다. 이를 위하여 지상형 산란계 시스템을 이용하여 옥수수 밭의 후방 산란 계수를 측정하였으며, 지표면 정보를 입력변수로 한 1차 VRT(Vector Radiative Transfer) 기법을 이용하여 후방 산란 계수를 계산하여 측정값과 비교/분석한다. 그 결과, 생육 초기에는 옥수수보다 토양에서의 산란이 지배적이었으며, 옥수수의 밀도가 증가하면서 잎의 분포의 영향으로 입사각이 증가하면서 후방 산란 계수가 점차 상승하는 특징을 보였다. 측정 데이터와 1차 VRT 계산 오차는 평균 RMSE (Root Mean Square Error)가 VV-편파에서 1.32 dB이었고, HH-편파에서 0.99 dB이었다. 또한, 1차 VRT 계산을 통해 LAI (Leaf Area Index) 변화에 따른 작물과 토양에서의 산란 영향을 분석하였다.

Keywords

References

  1. S. Said, U. C. Kothyari, and M. K. Arora, "Vegetation effects on soil moisture estimation from ERS-2 SAR images", Hydrolog. Sci. J., vol. 57, no. 3, pp. 517-534, Mar. 2012. https://doi.org/10.1080/02626667.2012.665608
  2. J. F. Paris, "The effect of leaf size on the microwave backscattering by corn", Remote Sens. Environ., vol. 19, no. 1, pp. 81-95, Feb. 1986. https://doi.org/10.1016/0034-4257(86)90042-8
  3. N. S. Chauhan, "Soil moisture inversion at L-band using a dual-polarization technique: a model-based sensitivity analysis", Int. J. Remote Sens., vol. 23, no. 16, pp. 3209-3227, Nov. 2002. https://doi.org/10.1080/01431160210136597
  4. E. P. W. Attema, F. T. Ulaby, "Vegetation modeled as a water cloud", Radio Sci., vol. 13, no. 2, pp. 357-364, Mar.-Apr. 1978. https://doi.org/10.1029/RS013i002p00357
  5. F. T. Ulaby, R. K. Moore, and A. K. Fung, Microwave Remote Sensing: Active and Passive, Artech House.
  6. L. Tsang, J. A. Kong, and R. T. Shin, Theory fo Microwave Remote Sensing, 1st ed. Hoboken, NJ: Wiley, 1985.
  7. S. -K. Kweon, J. -H. Hwang, and Y. Oh, "Development of a scattering model for soybean fields and verification with scatterometer and SAR data at X-band", Journal of Electromagnetic Engineering and Science, vol. 12, no. 1, pp. 115-121, Mar. 2012. https://doi.org/10.5515/JKIEES.2012.12.1.115
  8. Y. Oh, K. Sarabandi, and F. T. Ulaby, "Semi-empirical model of the emsemble-averaged differential mueller matrix for microwave backscattering from bare soil surfaces", IEEE Trans. Geosci. Remote Sensing, vol. 30, no. 6, pp. 1348-1355, Jun. 2002.
  9. 황지환, 이경엽, 박성민, 오이석, "X-밴드용 완전 편파 Scatterometer 설계", 한국전자파학회논문지, 20(12), pp. 1308-1315, 2009년 12월. https://doi.org/10.5515/KJKIEES.2009.20.12.1308
  10. 황지환, 박성민, 권순구, 오이석, "X-밴드 완전 편파 Scatterometer 시스템 보정에 관한 연구", 한국전자파학회논문지, 21(4), pp. 408-416, 2010년 4월. https://doi.org/10.5515/KJKIEES.2010.21.4.408
  11. 권순구, 황지환, 오이석, 홍성욱, "지표면 산란 계수 예측을 위한 정확한 지표면 거칠기 변수 측정 방법 및 오차 분석", 한국전자파학회논문지, 24(1), pp. 91- 97, 2013년 1월. https://doi.org/10.5515/KJKIEES.2013.24.1.91
  12. T. B. A. Senior, K. Sarabandi, and F. T. Ulaby, "Measuring and modeling the backscattering cross section of a leaf", Radio Sci., vol. 22, no. 6, pp. 1109-1116, Dec. 1987. https://doi.org/10.1029/RS022i006p01109