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, 2017, Vol. 14, No. 7, pp. 100-118

First application of Russian Meteor-M2 satellite for remote sensing of moisture and temperature of the tundra soil

K.V. Muzalevskiy 1 , Z.Z. Ruzicka 1 , I.V. Savin 1, 2 , M.G. Zahvatov 3 , V.V. Goncharov 4 , A.Kh. Sariev 4 , A.Yu. Karavaysky 1 
1 L.V. Kirensky Institute of Physics SB RAS, Krasnoyarsk, Russia
2 Peoples’ Friendship University of Russia, Moscow, Russia
3 Siberian Center of SRC "Planeta", Novosibirsk, Russia
4 Scientific Research Institute of Agriculture and Environment of the Arctic, Norilsk, Russia
Accepted: 29.08.2017
DOI: 10.21046/2070-7401-2017-14-7-100-118
This paper presents the results of remote sensing of temperature and moisture of thawed tundra soil on two test sites of the Taimyr Peninsula using polarimetric observations of the brightness temperature at a frequency of 10.7 GHz by the MTVZA-GY radiometer of the Meteor-M2 satellite. The footprints of the MTVZA-GY radiometer were chosen in the areas of Norilsk and Khatanga cities on the Taimyr Peninsula. The study covers the period from January 1 to December 31, 2015. The retrieving method of soil temperature and soil moisture is based on solving an inverse problem by minimizing the norm between observed and calculated values of the brightness temperature. The calculation of the brightness temperature was carried out using a semi-empirical model of microwave emission, the parameters of which were previously calibrated on the test areas of Norilsk and Khatanga cities, as well as using permittivity model of tundra soil with a high content of organic matter. The permittivity model of tundra soil was created in laboratory conditions using methods of dielectric spectroscopy and soil samples, which were taken at a test area close to Norilsk city. The root-mean-square error between the retrieved and measured values of soil temperature (soil moisture) were no more than 6.5°C (0.06 cm3/cm3). The obtained results indicates the prospect of using polarimetric observations of the brightness temperature at a frequency of 10.7 GHz by the MTVZA-GY radiometer on Russian Meteor-M2 satellite to measure the surface temperature and moisture of the Arctic tundra soil.
Keywords: Meteor-M, microwave radiometry, model of soil microwave emission, soil temperature, soil moisture, the Arctic zone
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References:

  1. Otsenochnyi doklad ob izmeneniyakh klimata i ikh posledstviyakh na territorii Rossiiskoi Federatsii. V 2-kh tomakh (Evaluative report on climate changes and its consequences on the territory of the Russian Federation. In two volumes). Moscow: Rosgidromet, 2008. Vol. 1, pp. 230–291, http://climate2008.igce.ru/v2008/htm/index00.htm/.
  2. Al-Yaari A., Wigneron J.P., Ducharne A., Kerr Y., de Rosnay P., de Jeu R., Govind A., Al Bitar A., Albergel C., Munoz-Sabater J., Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates, Remote Sensing of Environment, 2014, Vol. 149, pp. 181–195.
  3. Basharinov A., Shutko A., Simulation studies of the SHF radiation characteristics of soils under moist conditions, NASA Technical Translation, 1975, TT F-16.
  4. Bircher S., Demontoux F., Razafindratsima S., Zakharova E., Drusch M., Wigneron J.-P., Kerr Y.H., L-Band Relative Permittivity of Organic Soil Surface Layers — A New Dataset of Resonant Cavity Measurements and Model Evaluation, Remote Sens., 2016, Vol. 8, No. 12, pp. 1–17.
  5. Chukhlantsev A.A., Microwave radiometry of vegetation canopies, Dordrecht, The Netherlands: Springer, 2006, 287 p.
  6. 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 Trans. Geoscience and Remote Sensing, 1985, Vol. GE-23, pp. 35–46.
  7. ESA Data User Element. GlobCover Map. 2017. http://due.esrin.esa.int/page_globcover.php.
  8. Gill P.E., Murray W., Wright M.H., Practical optimization, London: Academic Press, 1981, 401 p.
  9. Jones L.A., Kimball J.S., McDonald K.C., Chan S.T.K., Njoku E.G., Oechel W.C., Satellite Microwave Remote Sensing of Boreal and Arctic Soil Temperatures From AMSR-E, IEEE Trans. Geoscience and Remote Sensing, 2007, Vol. 45, No. 7, pp. 2004–2018.
  10. Kerr Y.H., Al-Yaari A., Rodriguez-Fernandez N., Parrens M., Molero B., Leroux D., Bircher S., Mahmoodi A., Mialon A., Richaume P., Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation, Remote Sensing of Environment, 2016, Vol. 180, pp. 40–63.
  11. Koike T., Description of the GCOM-W1 AMSR2. Soil Moisture Algorithm Descriptions of GCOM-W1 AMSR2 Level 1R and Level 2 Algorithms, Japan Aerospace Exploration Agency, Earth Observation Research Center, 2013, 119 p.
  12. 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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, Vol. 8, No. 9, pp. 4470–4477.
  13. Mironov V.L., Kosolapova L.G., Fomin S.V., Physically and mineralogically based spectroscopic dielectric model for moist soils, IEEE Trans. Geoscience and Remote Sensing, 2009, Vol. 47, No. 7, pp. 2059–2070.
  14. Mironov V.L., Savin I.V., Karavaysky A.Y., Dielectric model in the frequency range 0.05 to 15 GHz at temperatures −30°C to 25°C for the samples of organic soils and litter collected in Alaska, Yamal, and Siberian Taiga, Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, 2016, pp. 2684–2687.
  15. Mitnik L.M., Cherny I.V., Mitnik M.L., Chernyavskii G.M., Kuleshov V.P., Baranyuk A.V., The MTVZA-GYa radiometer on the Meteor-M no. 2 satellite: the first 10 months in an orbit, calibration of data and retrieval of geophysical parameters, Abstract Intern. Symposium “Atmospheric Radiation and Dynamics“(ISARD – 2015), Saint-Petersburg-Petrodvorets, 2015, pp. 23–25.
  16. Muskett R.R., Romanovsky V.E., Cable W.L., Kholodov A.L., Active-Layer Soil Moisture Content Regional Variations in Alaska and Russia by Ground-Based and Satellite-Based Methods, 2002 through 2014, International Journal of Geosciences, 2015, Vol. 6, pp. 12–41.
  17. Njoku E.G., AMSR Land Surface Parameters. Surface Soil Moisture, Land Surface Temperature, Vegetation Water Content. Algorithm theoretical basis document, California Institute of Technology, 1999, 47 p.
  18. Observing Systems Capability Analysis and Review Tool. Gap analyses by variable or by type of mission, 2017, URL: https://www.wmo-sat.info/oscar/gapanalyses?variable=96.
  19. O’Neill P., Chan S., Njoku E., Jackson T., Bindlish R., Soil moisture active passive (SMAP) algorithm theoretical basis document Level 2 and 3 soil moisture (passive) data products, California Institute of Technology, 2014, 77 p.
  20. Schwank M., Mätzler C., Wiesmann A., Wegmüller U., Pulliainen J., Lemmetyinen J., Rautiainen K., Derksen K., Toose P., Drusch M., Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: A Synthetic Analysis, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, Vol. 8, No. 8, pp. 3833–3845.
  21. http://www.wmo.int/pages/prog/gcos/Publications/GCOS-195_en.pdf.
  22. Wang J.R., Choudhury B.J. Remote sensing of soil moisture content over bare field at 1.4 GHz frequency, J. Geophysical Research, 1981, Vol. 86, pp. 5277–5282.
  23. Wang J.R., Schmugge T.J. An empirical model for the complex dielectric permittivity of soils as a function of water content, IEEE Trans. Geosciences Remote Sensing, 1980, Vol. 18, pp. 288–295.
  24. WMO Statement on the Status of the Global Climate in 2015, World Meteorological Organization, WMO-No. 1167, Chairperson, Publications Board, 2016, pp. 28.
  25. Ye N., Walker J.P., Guerschman J., Ryu D., Gurney R.J., Standing water effect on soil moisture retrieval from L-band passive microwave observations, Remote Sensing of Environment, 2015, Vol. 169, pp. 232–242.
  26. Zhou J., Dai F., Zhang X., Zhao S., Li M., Developing a temporally land cover-based look-up table (TL-LUT) method for estimating land surface temperature based on AMSR-E data over the Chinese landmass, International Journal of Applied Earth Observation and Geoinformation, 2015, Vol. 34, pp. 35–50.