Microwave Satellite Systems for Hydrological Monitoring

УДК 537.86:556+528.85

  • I.V. Khvostov Institute for Water and Environmental Problems SB RAS (Barnaul, Russia) Email: khvostov.iwep@ya.ru
Keywords: monitoring, radiometer, satellite data, hydrological phenomena

Abstract

This paper considers existing and promising satellite microwave radiometry systems suitable for the evaluation of geophysical (hydrological) parameters of atmosphere, ocean, and land. A comparative analysis is provided for data sets available for end-users. Algorithms and tools for processing and visualization of satellite data are discussed. The capabilities of modern satellite systems to perform specific tasks of remote sensing are described using the example of a river flood in the Altai region in 2014. Monitoring soil moisture of upper layers of soil on floodplains combined with meteorological forecasts allows assessment of the probability of river flooding at certain areas using values of maximum soil moisture capacity. The effect of changes in the physical properties of ice during its destruction is discussed. This effect has been discovered by analyzing the dynamics of daily satellite measurements of brightness temperatures. It can be considered as a harbinger of ice condition changes of large freshwater bodies. The analysis of brightness temperature seasonal variations is presented using the example of Lake Big Bear (Canada).

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Author Biography

I.V. Khvostov, Institute for Water and Environmental Problems SB RAS (Barnaul, Russia)

старший научный сотрудник

References

Stampoulis D., Andreadis K.M., Granger S.L., et al. Assessing hydro-ecological vulnerability using microwave radiometric measurements // Remote Sensing of Environment. 2016. Vol. 184. D01:10.1016/j.rse.2016.06.007.

Lorenz C., Montzka C., Jagdhuber T., et al. LongTerm and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data // Remote Sensing. 2018. Vol. 10 № 11. DOI: 10.3390/rs10111842.

Tikhonov V.V., Boyarskii D.A., Sharkov E.A. et al. Microwave Model of Radiation from the Multilayer “Ocean-atmosphere” System for Remote Sensing Studies of the Polar Regions // Progress in Electromagnetics Research B. 2014. Vol. 59. DOI: 10.2528/PIERB14021706.

Данилычев М.В., Кутуза Б.Г. Современные спутниковые радиометры микроволнового диапазона // VI Всероссийские Армандовские чтения. Муром, 2016.

Митник Л.М., Митник М.Л., Заболотских Е.В. Спутник Японии GCOM-W1: моделирование, калибровка и первые результаты восстановления параметров океана и атмосферы // Современные проблемы дистанционного зондирования Земли из космоса. 2013. Т. 10. № 3.

Maeda T., Kazumori M., Aonashi K., et al. Descriptions of GCOM-W1 AMSR2 Level 1R and Level 2 Algorithms. NDX-120015A // Japan Aerospace Exploration Agency. 2013.

Gaiser P.W., Germain P.W., Twarog E.M. et al. The WindSat Spaceborne Polarimetric Microwave Radiometer: Sensor Description and Early Orbit Performance // IEEE TGRS. 2004. Vol. 42. № 11. DOI:10.1109/TGRS.2004.836867.

Hilburn K.A., Meissner T., Wentz F.J., et al. Ocean Vector Winds From WindSat Two-Look Polarimetric Radiances // IEEE TGRS. 2016. Vol. 54. № 2. DOI: 10.1109/ TGRS.2015.2469633.

Zhang L., Yin X., Shi H., et al. Hurricane Wind Speed Estimation Using WindSat 6 and 10 GHz Brightness Temperatures // Remote sensing. Vol. 8. № 9. DOI: 10.3390/rs8090721.

Gutierrez, A., Castro, R., and Vieira P.: SMOS L1 Processor L1c Data Processing Model, DEIMOS Engenharia, Lisboa, Portugal. 2014

Ященко A.C., Бобров П.П. Особенности обработки данных SMOS Level 1С в задачах дистанционного зондирования // Современные проблемы дистанционного зондирования Земли из космоса. 2017. Т. 14. № 3. DOI: 10.21046/2070-7401-2017-14-3-78-91

Sahr, K., White, D., and Kimerling, A. J. Geodesic Discrete Global Grid System // Cartography and Geographic Information Science. 2003. V. 30. № 2.

Romanov A.N., Khvostov I.V. Microwave Remote Monitoring of Altai Catastrophic Flood Dynamics Using SMOS Data // IEEE Geoscience and Remote Sensing Letters. 2015. Vol. 12. № 10. DOI: 10.1109/LGRS.2015.2444592.

Хвостов И.В., Романов А.Н., Тихонов В.В. и др. Некоторые особенности микроволнового радиотеплового излучения пресноводных водоемов с ледовым покровом // Современные проблемы дистанционного зондирования Земли из космоса. 2017. Т. 14. № 4. DOI: 10.21046/20707401-2017-14-4-149-154.

Tikhonov V., Khvostov I., Romanov A., et al. Theoretical study of ice cover phenology at large freshwater lakes based on SMOS MIRAS data // The Cryosphere. 2018. Vol. 12. DOI: 10.5194/tc-12-2727-2018.

Published
2020-03-06
How to Cite
Khvostov I. Microwave Satellite Systems for Hydrological Monitoring // Izvestiya of Altai State University, 2020, № 1(111). P. 52-57 DOI: 10.14258/izvasu(2020)1-07. URL: http://izvestiya.asu.ru/article/view/%282020%291-07.