Zhurnal Radioelektroniki - Journal of Radio Electronics. eISSN 1684-1719. 2022. №11
Contents

Full text in Russian (pdf)

DOI: https://doi.org/10.30898/1684-1719.2022.11.15

DEPENDENCE OF THE REFLECTIVE PROPERTIES OF AGRICULTURAL SOILS

IN ULTRA-WIDE FREQUENCY BAND ON THE TYPE,

SURFACE ROUGHNESS AND MOISTURE PROFILES OF AGROSOILS

K.V. Muzalevskiy, S.V. Fomin, A.Yu. Karavayskiy

Kirensky Institute of Physics, Federal Research Center KSC Siberian Branch Russian Academy of Sciences

660036, Russia, Krasnoyarsk, Akademgorodok, 50, b. 38

The paper was received December 5, 2022.

Abstract. In this article, the impact of volumetric moisture from 0% to 40% (vertical moisture profiles), dry bulk density from 0.4 to 1.8 g/cm3, clay content from 0.15 to 0.55 g/g (agrosoil type), standard deviations heights of surface roughness from 0 to 4 cm of soil on the variations of reflection coefficient in the ultra-wide frequency band from 100-400 MHz to 1.26-2.4 GHz were investigated. The reflection coefficient was calculated for a smooth and rough soil surface. Mironov's two-relaxation dielectric model was used (input parameters: dry bulk density, clay content, volumetric moisture, frequency of electromagnetic wave) to calculating the reflection coefficient. It is shown that the reflection coefficient is an ambiguous function of the clay content and the dry bulk density; the error in retrieving high values of soil moisture can be 5 times higher than for dry soils. In relation to the clay content and the dry bulk density, the soil roughness is the dominant parameter, which uncertainty, significantly effects on the error of soil moisture retrieving. For the considered various vertical profiles of soil moisture, it is shown that the effective thickness of topsoil, which forms the reflection coefficient, does not exceed 2 cm at a sensing frequency above 1 GHz. When the volumetric moisture content of soil surface is more than 28%, the reflection coefficient in the frequency range from 433 MHz to 1.26 GHz does not depend on the vertical distribution of moisture in soil. The conducted studies establish quantitative limitations on the accuracy of soil moisture retrieval for a given error in the initial parameters of the model: the clay content, the dry bulk density, soil surface roughness, which should be taken into account when developing algorithms for remote sensing of agrosoil moisture.

Key words: remote sensing, reflectometry, reflection coefficient, complex permittivity of soils, remote sensing of soil moisture.

Financing: The work was supported within the framework of the Russian Science Foundation and the Krasnoyarsk Regional Science Foundation grant No. 22-17-20042

Corresponding author: Muzalevskiy Konstantin Viktorovich, rsdkm@ksc.krasn.ru

References

1. Voronovich A.G., Lataitis R.J. Soil Moisture Profile Retrievals Using Reflection of Multifrequency Electromagnetic Signals. IEEE Transactions on Geoscience and Remote Sensing. 2022. V.60. №2006510. P.1-10. https://doi.org/10.1109/TGRS.2022.3204522

2. Voronovich A.G., Lataitis R.J. Soil Moisture Retrieval Using Reflection Coefficients: Numerical Experiments. IEEE Transactions on Geoscience and Remote Sensing. 2021. V.59. №11. P.8957-8967. https://doi.org/10.1109/TGRS.2020.3037012

3. Minet J., Wahyudi A., Bogaert P., et al. Mapping shallow soil moisture profiles at the field scale using full- waveform inversion of ground penetrating radar data. Geoderma. 2011. V.161. №3-4. P.225-237. https://doi.org/10.1016/j.geoderma.2010.12.023

4. Muzalevskii K.V. Remote sensing of moisture profiles in the arable soil layer based on polarimetric observations of the reflection coefficient in the P- and C-bands. Experimen. Eksperiment. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of Earth remote sensing]. 2020. V.17. №3. P.145-148. https://doi.org/10.21046/2070-7401-2020-17-3-145-148 (in Russian)

5. Muzalevskiy K.V. Retrieving soil moisture profiles based on multifrequency polarimetric radar backscattering observations. Theoretical case study. International Journal of Remote Sensing. 2021 V.42. №2. P.506-519. https://doi.org/10.1080/01431161.2020.1809743

6. Muzalevskiy K.V. A new method for remote sensing of moisture profiles in the arable layer at three frequencies; experimental case study. International Journal of Remote Sensing. 2021. V.42. №7. P.2377-2390. https://doi.org/10.1080/01431161.2020.1851795

7. Bobrov P.P., Belyaeva T.A., Kroshka E.S., Rodionova O.V. The Effect of Dielectric Relaxation Processes on the Complex Dielectric Permittivity of Soils at Frequencies From 10 kHz to 8 GHz - Part I: Experimental. IEEE Transactions on Geoscience and Remote Sensing. 2022. V.60. №2005409. P.1-9. https://doi.org/10.1109/TGRS.2022.3180727

8. Ulaby F.T., Long D.G. Microwave Radar and Radiometric Remote Sensing. The University of Michigan Press: Ann Arbor, MI, USA. 2013. 1116 p.

9. Bruggeman D. A. G. Berechnung verschiedemer physikalischer Konstanten von hetarogenen Substanzen. Ann. Phys. 1935. V.416. №7. P.636-679.

10. de Loor G.P. Dielectric Properties of Heterogeneous Mixtures Containing Water. Journal of Microwave Power. 1968. V.3. №2. P.67-73.

11. Birchak J.R., Gardner C.G., Hipp J.E., Victor J.M. High dielectric constant microwave probes for sensing soil moisture. Proceedings of the IEEE. 1974. V.62. №1. P.93-98. https://doi.org/10.1109/PROC.1974.9388

12. Dobson M.C., Ulaby F.T., Hallikainen M.T., El-rayes M.A. Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models. IEEE Transactions on Geoscience and Remote Sensing. 1985. V.GE-23. №1. P.35-46. https://doi.org/10.1109/TGRS.1985.289498

13. Peplinski N.R., Ulaby F.T., Dobson M.C. Dielectric properties of soils in the 0.3-1.3-GHz range. IEEE Transactions on Geoscience and Remote Sensing. 1995. V.33. №3. P.803-807. https://doi.org/10.1109/36.387598

14. Wang J.R., Schmugge T.J. An Empirical Model for the Complex Dielectric Permittivity of Soils as a Function of Water Content. IEEE Transactions on Geoscience and Remote Sensing. 1980. V.GE-18. №4. P.288-295. https://doi.org/10.1109/TGRS.1980.350304

15. Boyarskii D.A., Tikhonov V.V., Komarova N.Yu. Model of Dielectric Constant of Bound Water in Soil for Applications of Microwave Remote Sensing. Progress In Electromagnetics Research. 2002. V.35. P.251-269. https://doi.org/10.1163/156939302X01227

16. Park C.-H. et al. New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves. Remote Sensing. 2017. V.9. №7. P.732. https://doi.org/10.3390/rs9070732

17. Mironov V.L., Kosolapova L.G., Fomin S.V. Physically and Mineralogically Based Spectroscopic Dielectric Model for Moist Soils. IEEE Transactions on Geoscience and Remote Sensing. 2009. V.47. №7. P.2059-2070. https://doi.org/10.1109/TGRS.2008.2011631

18. Wigneron J.-P. et al. Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms. Remote Sensing of Environment. 2017. V.192. P.238-262. https://doi.org/10.1016/j.rse.2017.01.024

19. Zeng J., Chen K.S., Bi H. and Chen Q. A Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product Over United States and Europe Using Ground-Based Measurements. IEEE Transactions on Geoscience and Remote Sensing. 2016. V.54. №8. P.4929-4940. https://doi.org/10.1109/TGRS.2016.2553085

20. Zhang L., Meng Q., Hu D., Zhang Y., Yao S., Chen X. Comparison of different soil dielectric models for microwave soil moisture retrievals. International Journal of Remote Sensing. 2020. V.41. №8. P.3054-3069. https://doi.org/10.1080/01431161.2019.1698077

21. Guo P., Shi J., Gao B., Wan H. Evaluation of errors induced by soil dielectric models for soil moisture retrieval at L-band. Proceedings of IEEE International Geoscience and Remote Sensing Symposium. 2016. P.1679-1682. https://doi.org/10.1109/IGARSS.2016.7729429

22. Liu J, Liu Q. Soil Moisture Estimate Uncertainties from the Effect of Soil Texture on Dielectric Semiempirical Models. Remote Sensing. 2020. V.12. №14. P.2343. https://doi.org/10.3390/rs12142343

23. Mironov V.L., Bobrov P.P., Fomin S.V. Dielectric model of moist soils with varying clay content in the 0.04 to 26.5 GHz frequency range. Proceedings of International Siberian Conference on Control and Communications. 2013. P.1-4. https://doi.org/10.1109/SIBCON.2013.6693613

24. Yayong S., et al. Preliminary Applicability Analysis of Soil Dielectric Constant Model of the Different Soil Texture Condition. Proceedings of IEEE International Geoscience and Remote Sensing Symposium. 2019. P.7148-7151. https://doi.org/10.1109/IGARSS.2019.8900240

25. Hallikainen M.T., Ulaby F.T., Dobson M.C., et al. Microwave dielectric behavior of wet soil-part I: empirical models and experimental observations. IEEE Transactions on Geoscience & Remote Sensing. 1985. V.23. №1. P.25-34. https://doi.org/10.1109/TGRS.1985.289497

26. Mironov V.L., Fomin S.V., Lukin Yu.I. Three-relaxation generalized refractive dielectric model of wet soils. Izvestiya vysshikh uchebnykh zavedenii. Fizika [Russian Physics Journal]. 2015. V.58. №8-2. P.28-31. (in Russian)

27. Stogryn A. Equations for Calculating the Dielectric Constant of Saline Water (Correspondence). IEEE Transactions on Microwave Theory and Techniques. 1971. V.19. №8. P.733-736. https://doi.org/10.1109/TMTT.1971.1127617

28. Muzalevskii K.V. Broadband reflectometric method for measuring moisture and soil surface roughness. Zhurnal radioelektroniki [Journal of Radio Rlectronics] [online]. 2022. № 12. (in the editorial)

29. Muzalevskiy K.V. Numerical-Analytical Model of Reflection Coefficient for Rough Soil Surface in Wide Frequency Range. Proceedings of 8th All-Russian Microwave Conference (RMC). 2022. P.1-4.

30. Brekhovskikh L.M. Volny v sloistykh sredakh [Waves in layered media]. Moscow, Izd-vo Akademii nauk SSSR. 1957. 503 p. (in Russian)

For citation:

Muzalevskiy K.V., Fomin S.V., Karavayskiy A.Yu. Dependence of the reflective properties of agricultural soils in ultra-wide frequency band on the type, surface roughness and moisture profiles of agrosoils. Zhurnal radioelektroniki [Journal of Radio Electronics] [online]. 2022. №11. https://doi.org/10.30898/1684-1719.2022.11.15 (In Russian)