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Article information
2020 , Volume 25, ¹ 4, p.58-68
Dagurov P.N., Dmitriev A.V., Dobrynin S.D., Chimitdorzhiev T.N.
Estimation of snow cover parameters on the earth's surface with flat and hilly-mountainous terrain using radar interferometry
The main characteristics of the snow cover determining its impact on the environment are its thickness and the snow water equivalent (SWE). SWE assesses the water content in the snow cover. Radar interferometry is one of the methods for determining SWE. The paper presents the results of snow cover sensing by radar interferometry on both flat Earth’s surface and terrain with relief. A backscattering model taking into account backscattering from the snow surface is proposed in contrast to the existing methods. The backscattering field is considered as a coherent sum of waves scattered on the irregularities of the air — snow and snow — soil interfaces. These interfaces are statistically rough surfaces with random irregularities, whose heights are described by uncorrelated stationary random functions with their mean values, standard deviations, and correlation radii. It is assumed that the irregularities are small compared to the wavelength, their slopes are small, and the conditions for the applicability of the method of small perturbations are satisfied. It is also supposed that roughness does not affect the coherent field according to the Born approximation. The incident and scattered waves are assumed to follow Snell’s law. The coherent waves reflection and transmission coefficients are determined by Fresnel formulas for a flat interface. The contribution of backscattering from the snow surface to the values of the amplitude and interferometric phase is estimated using small perturbation method. It is shown that the relative error of interferometric phase determination due to the influence of the wave scattered by the air — snow boundary does not exceed 8% for the angles of incidence of 20–45∘ and the density of snow 0.2–0.3 g/cm3. The approximate relations show the linear dependence between the interferometric phase and SWE. The model is extended to the general case of backscattering from snow cover on the Earth’s surface with relief. The influence of terrain slopes on the interferometric phase is estimated. It is shown that for hilly terrain with slopes of about 45∘, the relative changes in the interferometric phase could reach 40%. However, if the slopes are relatively flat (less than 10∘), these changes do not exceed 10%
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Keywords: snow water equivalent, radar interferometry, small perturbation method, relief
doi: 10.25743/ICT.2020.25.4.006
Author(s):
Dagurov Pavel Nikolaevich
Dr. , Associate Professor
Position: Leading research officer
Office: Institute of Physical Material Science of the SB RAS
Address: 670047, Russia, Ulan-Ude, 6, Sakhyanovoy str.
Phone Office: (3012) 434819
E-mail: pdagurov@gmail.com
SPIN-code: 4015-9893Dmitriev Aleksey Valer'evich
PhD.
Position: Senior Research Scientist
Office: Institute of physical materials science SB RAS
Address: 670047, Russia, Ulan-Ude, Sakhyanovoy St., 6
Phone Office: (3012) 434-819
E-mail: dav@ipms.bscnet.ru
SPIN-code: 6686-0205Dobrynin Sergey Dobrynin Sergey Innokentevich
Position: Head of department
Office: Buryat Institute of Infocommunications
Address: 670031, Russia, Ulan-Ude, Trubacheeva str., 152
Phone Office: (3012)240024
E-mail: dobrynin@biik.ru
Chimitdorzhiev Tumen Namzhilovich
Dr. , Professor
Position: Head of Sector
Office: Institute of Physical Material Science of the SB RAS
Address: 670047, Russia, Ulan-Ude, 6, Sakhyanovoy str.
Phone Office: (3012) 416981
E-mail: tchimit@ipms.bscnet.ru
SPIN-code: 3968-0614 References:
1. Rees W.G. Remote sensing of snow and ice. CRC Press, Taylor & Francis Group; 2006: 302.
2. Moreira A., Prats-Iraola P., Younis M., Krieger G., Hajnsek I., Papathanassiou K. A tutorial onsynthetic aperture radar. IEEE Geosci. Remote Sensing Mag. 2013; 1(1):6–43.
3. Hanssen R.F. Radar interferometry: Data interpretation and error analysis. Dordrecht: Kluwer AcademicPublishers; 2001: 308.
4. Zakharov A.I., Epov M.I., Mironov V.L., Chymitdorzhiev T.N., Bykov M.E., Seleznev V.S., Emanov A.F.,Cherepenin V.A. Earth surface subsidence in the Kuznetsk coal basin caused by manmade and natural seismic activity according to ALOS PALSAR interferometry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2013; 6(3):1578–1583.
5. Beck I., Ludwig R., Bernier M., Strozzi T., Boike J. Vertical movements of frost mounds in subArctic permafrost regions analyzed using geodetic survey and satellite interferometry. Earth Surface Dynamics. 2015; (3):409–421.
6. Chimitdorzhiev T.N., Dagurov P.N., Bykov M.E., Dmitriev A.V., Kirbizhekova I.I. Comparison of ALOS PALSAR interferometry and field geodetic leveling for marshy soil thaw/freeze monitoring, case study from the Baikal lake region, Russia. Journal of Applied Remote Sensing. 2016; 10(1):016006.
7. Guneriussen T., Hogda K.A., Johnsen H., Lauknes I. InSAR for estimation of changes in snowwater equivalent of dry snow. IEEE Transactions on Geoscience and Remote Sensing. 2001; 39(10): 2101–2108.
8. Rott H., Nagler T., Scheiber R. Snow mass retrieval by means of SAR interferometry. 2003. Availableat: https://earth.esa.int/fringe03/proceedings/papers/46_rott.pdf (accessed 18.03.2020).
9. Leinss S., Wiesmann A., Lemmetyinen J., Hajnsek I. Snow water equivalent of dry snow measuredby differential interferometry. IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. 2015; 8(8): 3773–3790.
10. Conde V., Nico G., Mateus P., Catalao J., Kontu A., Gritsevich M. On the estimation of temporalchanges of snow water equivalent by spaceborne SAR interferometry: a new application for the Sentinel-1 mission. J. Hydrol. Hydromech. 2019; 67(1):93–100.
11. Dagurov P.N., Chimitdorzhiev T.N., Dmitriev A.V., Dobrynin S.I., Zakharov A.I., Baltukhaev A.K.,Bykov M.E., Kirbizhekova I.I. Determination of snow cover parameters by means of L-band radar differential interferometry. Journal of Radio Electronics. 2017; (5). Available at: http://jre.cplire. ru/jre/may17/1/text.pdf (accessed 18.03.2020). (In Russ.)
12. Dagurov P.N., Baltukhaev A.K., Dmitriev A.V., Dobrynin S.I., Chimitdorzhiev T.N. Interferometricheskaya model’ radarnogo zondirovaniya snezhnogo pokrova. Regional’nye problemy distantsionnogo zondirovaniya Zemli. Materialy V Mezhd. nauchn. konferentsii. Proc. of the Intern. Conf. “Regional problems of remote sensing of the Earth”. Krasnoyarsk: SFU, Institut kosmicheskikh i informatsionnykh tekhnologiy; 2018: 109–112. (In Russ.)
13. Ulaby F.T., Moore R.K., Fung A.K. Microwave remote sensing. Dedham, MA: Artech House; 1982. Chapter 12. Vol. 2.
14. Matzler C. Microwave permittivity of dry snow. IEEE Trans. Geosci. Remote Sens. 1996; 34(2): 573–581.
Bibliography link:
Dagurov P.N., Dmitriev A.V., Dobrynin S.D., Chimitdorzhiev T.N. Estimation of snow cover parameters on the earth's surface with flat and hilly-mountainous terrain using radar interferometry // Computational technologies. 2020. V. 25. ¹ 4. P. 58-68
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