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Surface Parameter Inversion of Polarimetric Synthetic Aperture Radar Data

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Polarimetric Microwave Imaging

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Abstract

Soil moisture inversion using polarimetric SAR data is an important contribution of polarized microwave imaging radars in hydrogeography, meteorology, and agricultural process economic optimization. The main difficulty in quantitatively estimating soil moisture or surface roughness is how to separate their effects on radar backscatter. In order to accurately estimate soil moisture, surface roughness information is often required. It is not possible to estimate the surface roughness independently using only one frequency or one polarization SAR data, and roughness is considered as an interference factor for soil moisture estimation. This chapter will describe the methods for estimating surface roughness and soil moisture independently from fully polarized SAR data.

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References

  1. L.-S. Lee, D.L. Schuler, Polarimetric SAR data compensation for terrain azimuth slope variation. IEEE Trans. GRS 38(5), 2153–2163 (2000)

    Google Scholar 

  2. L.H. Ulander, Radiometric slope correction of synthetic aperture radar images. IEEE. Trans. GRS 34(5), 1115–1122 (1996)

    Google Scholar 

  3. D.L. Schuler, J.-S. Lee, T.L. Ainsworth, W.M. Boerner, Correction for terrain azimuthal slope effects in polarimetric SAR images, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000, vol. 3 (2000), pp. 1304–1306

    Google Scholar 

  4. P.E. O’Neill, A.Y. Hsu, M.S. Seyfried, SAR terrain correction for improved soil moisture estimation in a mountain watershed, in Geoscience and Remote Sensing Symposium, 1994. IGARSS ‘94, vol. 3 (1994), pp. 1429–1431

    Google Scholar 

  5. G. Riegler, W. Mauser, Geometric and radiometric terrain correction of ERS SAR data for applications in hydrologic modelling, in Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS ‘98, vol. 5 (1998), pp. 2603–2605

    Google Scholar 

  6. I. Hajnsek, E. Pottier, Terrain correction for quantitative moisture and roughness retrieval using polarimetric SAR data, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000, vol. 3 (2000), pp. 1307–1309

    Google Scholar 

  7. J.T. Parr, Geometric transformation and terrain correction of remotely-sensed imagery, in Geoscience and Remote Sensing Symposium, 1989. IGARSS’89, vol. 2 (1989), pp. 440–441

    Google Scholar 

  8. H.A. Zebker, J.J. Van Zyl, S.L. Durden, L. Norikane, Calibrated imaging radar polarimetry: technique, examples, and applications. IEEE Trans. GRS 29(6), 942–961 (1991)

    Google Scholar 

  9. M.S. Dawson, J. Olvera, A.K. Fung, M.T. Manry, Inversion of surface parameters using fast learning neural networks, in Geoscience and Remote Sensing Symposium, 1992. IGARSS ‘92, vol. 2 (1992), pp. 910–912

    Google Scholar 

  10. I. Hajnsek, S.R. Cloude, J.-S. Lee, E. Pottier, Inversion of surface parameters from polarimetric SAR data, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000, vol. 3 (2000), pp. 1095–1097

    Google Scholar 

  11. M. Moghaddam, S. Saatchi, An inversion algorithm applied to SAR data to retrieve surface parameters, in Geoscience and Remote Sensing Symposium, 1993. IGARSS ‘93, vol. 2 (1993), pp. 587–589

    Google Scholar 

  12. K.S. Chen, Y.C. Tzeng, W.L. Kao, Retrieval of surface parameters using dynamic learning neural network, in Geoscience and Remote Sensing Symposium, 1993. IGARSS ‘93. ‘Better Understanding of Earth Environment’, vol. 2 (1993), pp. 505–507

    Google Scholar 

  13. R. Hoeben, P.A. Troch, Z. Su, M. Mancini, K.-S. Chen, Sensitivity of radar backscattering to soil surface parameters: a comparison between theoretical analysis and experimental evidence, in Geoscience and Remote Sensing, 1997. IGARSS’97, vol. 3 (1997), pp. 1368–1370

    Google Scholar 

  14. E.G. Njoku, A. Chehbouni, F. Cabot, B. Rague, K. Fleming, Y.H. Kerr, An approach to estimating surface parameters and fluxes using modeling and multispectral remote sensing, in Geoscience and Remote Sensing Symposium, 1994. IGARSS ‘94, vol. 1 (1994), pp. 187–189

    Google Scholar 

  15. S.Foucher, F. Zagolski, C. Gaillard, Y. Voirin, M.N. Nguyen, Influence of speckle filtering on the assessment of agricultural surface parameters, in Geoscience and Remote Sensing Symposium, 1999. IGARSS ‘99 Proceedings, vol. 4 (1999), pp. 2137–2139

    Google Scholar 

  16. E.D. Hernandez-Baquero, J.R. Schott, Atmospheric and surface parameter retrievals from multispectral thermal imagery via reduced-rank multivariate regression, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000, vol. 4 (2000), pp. 1525–1527

    Google Scholar 

  17. A. Ishimaru, J.-N. Hwang, K. Yoshitomi, J.-S. Chen, Application of artificial neural network (ANN) technique to rough surface inverse scattering problems, in Antennas and Propagation Society International Symposium, 1992. AP-S. 1992 Digest, vol. 3 (1992), pp. 1397

    Google Scholar 

  18. Y.-A. Liou, Y.C. Tzeng, A.W. England, Retrieval of soil moisture using a dynamic learning neural network trained with a 1-dimensional hydrology/radiobrightness model, in Geoscience and Remote Sensing, 1997. IGARSS ‘97, vol. 3 (1997), pp. 1096–1098

    Google Scholar 

  19. Y. Oh, K. Sarabandi, F.T. Ulaby, An inversion algorithm for retrieving soil moisture and surface roughness from polarimetric radar observation, in Geoscience and Remote Sensing Symposium, 1994. IGARSS ‘94, vol. 3 (1994), pp. 1582–1584

    Google Scholar 

  20. I. Hajnsek, E. Pottier, S.R. Cloude, Inversion of surface parameters from polarimetric SAR. IEEE Trans. GRS 41(4), 727–744

    Google Scholar 

  21. D.L. Schuler, J.S. Lee, D. Kasilingam, G. Nesti, Remote sensing of surface roughness using polarimetric SAR data, in Geoscience and Remote Sensing Symposium, 2001. IGARSS ‘01, vol. 2 (2001), pp. 916–918

    Google Scholar 

  22. Z. Li, K. Feng, Inversion of soil moisture and complex dielectric constant from radar backward scattering coefficient. Sci. China Ser. E Inf. Sci. 27(3), 223–228 (1997)

    Google Scholar 

  23. L. Sagues, X. Fabregas, A. Broquetas, Extraction of vegetation structure and surface parameters using polarimetric and interferometric SAR techniques, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000, vol. 1 (2000), pp. 141–143

    Google Scholar 

  24. X. Liu, Studies on Information Processing Technique of Fully-Polarimetric Synthetic Aperture Radar. Institute of Electronics, Chinese Academy of Sciences, Ph.D. 2004.01

    Google Scholar 

  25. I. Hajnsek, K.P. Papathanassiou, S.R. Cloude, L- and P-band for surface parameter estimation, in Geoscience and Remote Sensing Symposium, 2001. IGARSS ‘01, vol. 6 (2001), pp. 2775–2777

    Google Scholar 

  26. I. Hajnsek, K.P. Papathanassiou, A. Moreira, S.R. Cloude, Surface parameter estimation using interferometric and polarimetric SAR, in Geoscience and Remote Sensing Symposium, 2002. IGARSS ‘02, vol. 1 (2002), pp. 420–422

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Electronics, Chinese Academy of Sciences, Beijing, China

    Ruliang Yang

  2. Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China

    Bowei Dai

  3. East China Research Institute of Electronics Engineering, Hefei, China

    Lulu Tan

  4. Institute of Electronics, Chinese Academy of Sciences, Beijing, China

    Xiuqing Liu

  5. Institute of Electronics, Chinese Academy of Sciences, Beijing, China

    Zhen Yang

  6. National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China

    Haiying Li

Authors
  1. Ruliang Yang
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  2. Bowei Dai
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  3. Lulu Tan
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  4. Xiuqing Liu
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  5. Zhen Yang
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  6. Haiying Li
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Correspondence to Ruliang Yang .

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Yang, R., Dai, B., Tan, L., Liu, X., Yang, Z., Li, H. (2021). Surface Parameter Inversion of Polarimetric Synthetic Aperture Radar Data. In: Polarimetric Microwave Imaging. Springer, Singapore. https://doi.org/10.1007/978-981-15-8897-6_14

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  • DOI: https://doi.org/10.1007/978-981-15-8897-6_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8896-9

  • Online ISBN: 978-981-15-8897-6

  • eBook Packages: EngineeringEngineering (R0)

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