Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 4, pp. 155-165

Measurement of soil moisture and temperature based on interference reception of linearly-polarized GLONASS and GPS signals

K.V. Muzalevskiy 1 , M.I. Mikhailov 1 
1 L. V. Kirensky Institute of Physics SB RAS, Krasnoyarsk, Russia
Accepted: 10.07.2018
DOI: 10.21046/2070-7401-2018-15-4-155-165
This paper presents the results of a theoretical study of the potential for remote sensing of moisture of agricultural thawed soil, moisture and temperature in tundra frozen soil based on measurement of the ratio between reflection coefficients on linear-orthogonal polarizations (polarization index) from the interference patterns of GLONASS and GPS signals recorded near the Earth’s surface at frequencies of 1.2 and 1.6 GHz. The ranges of satellites elevation angles within which the coherent component exceeds the diffuse part in the mirror scattering of GLONASS and GPS signals by the surface roughness were estimated by Kirchhoff’s method. In the course of solving the direct problem, the “measured” polarization index of reflected waves was simulated (with addition of a random variable distributed according to the normal law) at two frequencies of 1.2 and 1.6 GHz using typical moisture and temperatures profiles of soils. It is shown that the polarization index is not sensitive enough to retrieve the layered structure of moisture in thawed and temperature profile in frozen soil, against the background noise (1.5–2 dB) of the recorded interference diagrams. The inverse problem of soil moisture and soil temperature retrieval from the “measured” polarization index was solved in the approximation of dielectrically-homogeneous half-space. It is shown that for all the profiles examined, regardless of frequency of GNSS signals, the maximum error in soil moisture and soil temperature retrieval does not exceed 0.03 cm3/cm3 and 1 °C, relative to the corresponding average values calculated for the topsoil of 1 cm.
Keywords: Global navigation satellite systems, GLONASS, GPS, reflectometry, soil moisture, soil temperature, agricultural soils, Arctic tundra soils
Full text

References:

  1. Arroyo A. A., Contributions to Land, Sea, and Sea-Ice Remote Sensing Using GNSS-Reflectometry, PhD thesis, Universitat Polit`ecnica de Catalunya, 2016, 424 p.
  2. Arroyo A.A, Camps A., Aguasca A., Forte G., Monerris A., Rüdiger C., Walker J. P., Park H., Pascual D., Onrubia R., Improving the Accuracy of Soil Moisture Retrievals Using the Phase Difference of the Dual-Polarization GNSS-R Interference Patterns, IEEE Geosci. Remote Sens. Lett., 2014, Vol. 11, No. 12, pp. 2090–2094.
  3. Beckman P., Spizzichino A., The Scattering of Electromagnetic Waves from Rough Surfaces, Elmsford, New York: Pergamon, 1963, 503 p.
  4. Brekhovskikh L. M., Waves in Layered Media, New York: Academic Press, 1960, 561 p.
  5. Carreno-Luengo H. Amèzaga A., Vidal D., Olivé R., Munoz J. F., Camps A., First Polarimetric GNSS-R Measurements from a Stratospheric Flight over Boreal Forests, Remote Sens., 2015, Vol. 7(10), pp. 13120–13138.
  6. Ceraldi E., Franceschetti G., Iodice A., Riccio D., Estimating the soil dielectric constant via scattering measurements along the specular direction, IEEE Transactions on Geoscience and Remote Sensing, 2005, Vol. 43, No. 2, pp. 295–305.
  7. Egido A., Paloscia S., Motte E, Guerriero L., Pierdicca N., Caparrini M., Santi E., Fontanelli G., Floury N., Airborne GNSS-R Polarimetric Measurements for Soil Moisture and Above-Ground Biomass Estimation, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2014, Vol. 7, No. 5, pp. 1522–1532.
  8. GLONASS interface control document. Navigational radiosignal. In bands L1, L2. (Edition 5.1), Moscow, 2008, 63 p.
  9. Larson K. M., GPS interferometric reflectometry: applications to surface soil moisture, snow depth, and vegetation water content in the western United States, Wiley Interdisciplinary Reviews: Water, 2016, Vol. 3, pp. 775–787.
  10. McCreight J. L., Small E. E., Larson K. M., Snow depth, density, and SWE estimates derived from GPS reflection data: Validation in the western U. S., Water Resour. Res., 2014, Vol. 50, pp. 6892–6909.
  11. Mironov V. L., Muzalevskiy K. V., The new algorithm for retrieval of soil moisture and surface roughness from GNSS reflectometry, Proc. IGARSS, Munich, 2012, pp. 7530–7532.
  12. 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, Vol. 47, No. 7, pp. 2059–2070.
  13. Mironov V. L., Kerr Y. H., Kosolapova L. G., Savin I. V., Muzalevskiy K. V., A Temperature-Dependent Dielectric Model for Thawed and Frozen Organic Soil at 1.4 GHz, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2015, Vol. 8, No. 9, pp. 4470–4477.
  14. Njoku E. G., Kong J.-A., Theory for passive microwave remote sensing of near‐surface soil moisture, J. Geoph. Res., 1977, Vol. 82, No. 20, pp. 3108–3118.
  15. Watanabe M., Kadosaki G., Kim Y., Ishikawa M., Kushida K., Sawada Y., Tadono T., Fukuda M., Sato M., Analysis of the Sources of Variation in L-band Backscatter From Terrains With Permafrost, IEEE Transactions on Geoscience and Remote Sensing, 2012, Vol. 50, No. 1, pp. 44–54.
  16. Zavorotny V. U., Voronovich A. G., Bistatic GPS signal reflections at various polarizations from rough land surface with moisture content, Proc. IGARSS, Honolulu, 2000, pp. 2852–2854.
  17. Zavorotny V. U., Gleason S., Cardellach E., Camps A., Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity, IEEE Geoscience and Remote Sensing Magazine, 2014, Vol. 2, No. 4, pp. 8–45.
  18. Zhang S., Roussel N., Boniface K., Cuong M., Frappart F., Darrozes J., Baup F., Calvet J.-C., Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop, Hydrol. Earth Syst. Sci., 2017, Vol. 21, pp. 4767–4784.