Vol. 170

Latest Volume
All Volumes
All Issues
2021-04-03

L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for SMAP Active Algorithms

By Huanting Huang, Tien-Hao Liao, Seung Bum Kim, Xiaolan Xu, Leung Tsang, Thomas J. Jackson, and Simon Yueh
Progress In Electromagnetics Research, Vol. 170, 129-152, 2021
doi:10.2528/PIER21020702

Abstract

Wheat, canola, and pasture are three of the major vegetation types studied during the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) conducted to support NASA's Soil Moisture Active Passive (SMAP) mission. The utilized model structure is integrated in the SMAP baseline active retrieval algorithm. Forward lookup tables (data-cubes) for VV and HH backscatters at L-band are developed for wheat and canola fields. The data-cubes have three axes: vegetation water content (VWC), root mean square (RMS) height of rough soil surface and soil permittivity. The volume scattering and doublebounce scattering of the fields are calculated using the distorted Born approximation and the coherent reflectivity in the double-bounce scattering. The surface scattering is determined by the numerical solutions of Maxwell equations (NMM3D). The results of the data-cubes are validated with airborne radar measurements collected during SMAPVEX12 for ten wheat fields, five canola fields, and three pasture fields. The results show good agreement between the data-cube simulation and the airborne data. The root mean squared errors (RMSE) were 0.82 dB, 0.78 dB, and 1.62 dB for HH, and 0.97 dB, 1.30 dB, and 1.82 dB for VV of wheat, canola, and pasture fields, respectively. The data-cubes are next used to perform the time-series retrieval of the soil moisture. The RMSEs of the soil moisture retrieval are 0.043 cm3/cm3, 0.082 cm3/cm3, and 0.082 cm3/cm3 for wheat, canola, and pasture fields, respectively. The results of this paper expand the scope of the SMAP baseline radar algorithm for wheat, canola, and pastures formed and provide a quantitative validation of its performance. It will also have applications for the upcoming NISAR (NASA-ISRO SAR Mission).

Citation


Huanting Huang, Tien-Hao Liao, Seung Bum Kim, Xiaolan Xu, Leung Tsang, Thomas J. Jackson, and Simon Yueh, "L-Band Radar Scattering and Soil Moisture Retrieval of Wheat, Canola and Pasture Fields for SMAP Active Algorithms," Progress In Electromagnetics Research, Vol. 170, 129-152, 2021.
doi:10.2528/PIER21020702
http://test.jpier.org/PIER/pier.php?paper=21020702

References


    1. Entekhabi, D., et al., "The Soil Moisture Active Passive (SMAP) mission," Proceedings of the IEEE, Vol. 98, 704-716, May 2010.
    doi:10.1109/JPROC.2010.2043918

    2. Entekhabi, D., S. Yueh, P. O’Neill, and K. Kellogg, SMAP Handbook, 400-1567, JPL Publication JPL, 2014.

    3. Tabatabaeenejad, A., M. Burgin, and M. Moghaddam, "Potential of L-band radar for retrieval of canopy and subcanopy parameters of boreal forests," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, 2150-2160, Jun. 2012.
    doi:10.1109/TGRS.2011.2173349

    4. Kellogg, K., et al., "NASA-ISRO Synthetic Aperture Radar (NISAR) mission," 2020 IEEE Aerospace Conference, 2020.

    5. Amelung, F., NASA-ISRO SAR (NISAR) Mission Science Users’ Handbook, Jet Propulsion Laboratory (U.S.), 2019.

    6. Stavros, N., P. Siqueira, M. Cosh, N. Torbick, and B. Osmanoglu, 2018 NISAR Applications Workshop: Agriculture and Soil Moisture, 2018.

    7. NISAR: The NASA-ISRO SAR MissWater: Vital for Life and Civilization, available: https://nisar.jpl.nasa.gov/system/documents/files/15 NISARApplications SoilMoisture1.pdf.

    8. Kim, Y. and J. J. Van Zyl, "A time-series approach to estimate soil moisture using polarimetric radar data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, 2519-2527, 2009.
    doi:10.1109/TGRS.2009.2014944

    9. Joseph, A. T., R. van der Velde, P. E. O’Neill, R. H. Lang, and T. Gish, "Soil moisture retrieval during a corn growth cycle using L-band (1.6 GHz) radar observations," IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, 2365-2374, 2008.
    doi:10.1109/TGRS.2008.917214

    10. De Roo, R. D., Y. Du, F. T. Ulaby, and M. C. Dobson, "A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion," IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, 864-872, Apr. 2001.
    doi:10.1109/36.917912

    11. Kim, S. B., L. Tsang, J. T. Johnson, S. Huang, J. J. van Zyl, and E. G. Njoku, "Soil moisture retrieval using time-series radar observations over bare surfaces," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, 1853-1863, May 2012.
    doi:10.1109/TGRS.2011.2169454

    12. Kim, S. B., M. Moghaddam, L. Tsang, M. Burgin, X. L. Xu, and E. G. Njoku, "Models of L-band radar backscattering coefficients over global terrain for soil moisture retrieval," IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, 1381-1396, Feb. 2014.
    doi:10.1109/TGRS.2013.2250980

    13. Mironov, V. L., M. C. Dobson, V. H. Kaupp, S. A. Komarov, and V. N. Kleshchenko, "Generalized refractive mixing dielectric model for moist soils," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, 773-785, Apr. 2004.
    doi:10.1109/TGRS.2003.823288

    14. Hallikainen, M. T., F. T. Ulaby, M. C. Dobson, M. A. Elrayes, and L. K. Wu, "Microwave dielectric behavior of wet soil. 1. Empirical-models and experimental-observations," IEEE Transactions on Geoscience and Remote Sensing, Vol. 23, 25-34, 1985.
    doi:10.1109/TGRS.1985.289497

    15. Kim, S.-B., et al., "Surface soil moisture retrieval using the L-band synthetic aperture radar onboard the Soil Moisture Active- Passive satellite and evaluation at core validation sites," IEEE Transactions on Geoscience and Remote Sensing, Vol. 55, 1897-1914, 2017.
    doi:10.1109/TGRS.2016.2631126

    16. Huang, H., et al., "Coherent model of L-band radar scattering by soybean plants: Model development, evaluation, and retrieval," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 9, 272-284, 2016.
    doi:10.1109/JSTARS.2015.2469717

    17. Liao, T. H., S. B. Kim, S. R. Tan, L. Tsang, C. X. Su, and T. J. Jackson, "Multiple scattering effects with cyclical correction in active remote sensing of vegetated surface using vector radiative transfer theory," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 9, 1414-1429, Apr. 2016.
    doi:10.1109/JSTARS.2015.2505638

    18. Lang, R. H. and J. S. Sidhu, "Electromagnetic backscattering from a layer of vegetation — A discrete approach," IEEE Transactions on Geoscience and Remote Sensing, Vol. 21, 62-71, 1983.
    doi:10.1109/TGRS.1983.350531

    19. Tsang, L., J. A. Kong, and R. T. Shin, Theory of Microwave Remote Sensing, Wiley, New York, 1985.

    20. Toure, A., K. P. B. Thomson, G. Edwards, R. J. Brown, and B. G. Brisco, "Adaptation of the mimics backscattering model to the agricultural context — Wheat and canola at L and C bands," IEEE Transactions on Geoscience and Remote Sensing, Vol. 32, 47-61, Jan. 1994.
    doi:10.1109/36.285188

    21. Ulaby, F. T., K. Sarabandi, K. Mcdonald, M. Whitt, and M. C. Dobson, "Michigan microwave canopy scattering model," International Journal of Remote Sensing, Vol. 11, 1223-1253, Jul. 1990.
    doi:10.1080/01431169008955090

    22. Tsang, L. and J. A. Kong, Scattering of Electromagnetic Waves, Advanced Topics, Vol. 26, John Wiley & Sons, 2004.

    23. Huang, H., et al., "Modelling and validation of combined active and passive microwave remote sensing of agricultural vegetation at L-band," Progress In Electromagnetics Research B, Vol. 78, 91-124, 2017.
    doi:10.2528/PIERB17060303

    24. Lang, R. H. and N. Khadr, "Effects of backscattering enhancement on soil-moisture sensitivity," International Space Year: Space Remote Sensing, Vol. 1 and 2, 916-919, 1992.

    25. Huang, S. and L. Tsang, "Electromagnetic scattering of randomly rough soil surfaces based on numerical solutions of Maxwell equations in three-dimensional simulations using a hybrid UV/PBTG/SMCG method," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, 4025-4035, 2012.
    doi:10.1109/TGRS.2012.2189776

    26. McNairn, H., et al., "The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch calibration and validation of the SMAP soil moisture algorithms," IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, 2784-2801, 2015.
    doi:10.1109/TGRS.2014.2364913

    27. Huang, H., L. Tsang, E. G. Njoku, A. Colliander, T.-H. Liao, and K.-H. Ding, "Propagation and scattering by a layer of randomly distributed dielectric cylinders using Monte Carlo simulations of 3D Maxwell equations with applications in microwave interactions with vegetation," IEEE Access, Vol. 5, 11985-12003, 2017.
    doi:10.1109/ACCESS.2017.2714620

    28. Huang, H., L. Tsang, A. Colliander, and S. H. Yueh, "Propagation of waves in randomly distributed cylinders using three-dimensional vector cylindrical wave expansions in Foldy-Lax equations," IEEE Journal on Multiscale and Multiphysics Computational Techniques, Vol. 4, 214-226, 2019.
    doi:10.1109/JMMCT.2019.2948022

    29. Gu, W. and L. Tsang, "Vegetation effects for remote sensing of soil moisture using NMM3D full-wave simulation," IEEE Antennas and Propagation Symposium, Montreal, 2020.

    30. Huang, H., et al., "Modelling and validation of combined active and passive microwave remote sensing of agricultural vegetation at L-band," Progress In Electromagnetics Research, Vol. 78, 91-124, 2017.
    doi:10.2528/PIERB17060303

    31. Ulaby, F. T., et al., Microwave Radar and Radiometric Remote Sensing, 2014.

    32. Tsang, L., J. Kong, and K.-H. Ding, "Scattering of Electromagnetic Waves: Theories and Applications," John Wisley & Sons, ed: Inc, 2000.

    33. Hensley, S., et al., "The UAVSAR instrument: Description and first results," 2008 IEEE Radar Conference, Vol. 1–4, 827-832, 2008.

    34. Mladenova, I. E., T. J. Jackson, R. Bindlish, and S. Hensley, "Incidence angle normalization of radar backscatter data," IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, 1791-1804, Mar. 2013.
    doi:10.1109/TGRS.2012.2205264

    35. Deng, H., G. Farquharson, J. Sahr, Y. Goncharenko, and J. Mower, "Phase calibration of an along-track interferometric FMCW SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 56, 4876-4886, 2018.
    doi:10.1109/TGRS.2018.2841837

    36. Rowlandson, T. L., et al., "Evaluation of several calibration procedures for a portable soil moisture sensor," Journal of Hydrology, Vol. 498, 335-344, Aug. 19, 2013.
    doi:10.1016/j.jhydrol.2013.05.021

    37. Cosh, M. H., T. J. Jackson, R. Bindlish, J. S. Famiglietti, and D. Ryu, "Calibration of an impedance probe for estimation of surface soil water content over large regions," Journal of Hydrology, Vol. 311, 49-58, Sep. 15, 2005.
    doi:10.1016/j.jhydrol.2005.01.003

    38. Ulaby, F. T. and M. A. Elrayes, "Microwave dielectric spectrum of vegetation. 2. Dual-dispersion model," IEEE Transactions on Geoscience and Remote Sensing, Vol. 25, 550-557, Sep. 1987.
    doi:10.1109/TGRS.1987.289833