Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 23, 2026
Number 1
Volume 22, 2025
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
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, 2026, V. 23, No. 1, pp. 231-244

Development of a geophysical model function for surface wind speed retrieval in conditions of Gorky Reservoir

O.S. Ermakova 1 , N.S. Rusakov 1 , E.I. Poplavsky 1 , O.A. Danilicheva 1 , G.A. Baidakov 1 , D.A. Sergeev 1 
1 Institute of Applied Physics RAS, Nizhny Novgorod, Russia
Accepted: 13.10.2025
DOI: 10.21046/2070-7401-2026-23-1-231-244
The paper is devoted to the development of a method for the retrieval of wind speed at a standard meteorological height based on electromagnetic scattering calculated within a two-scale model and verified using data from the Sentinel-1 C-band synthetic aperture radar (SAR) for direct VV polarization and collocated meteorological station measurements. The method is based on a new geophysical model function (GMF) representing the relationship between specific effective scattering cross-section and surface wind speed, incidence angle of microwave signal, wind direction, and wave fetch. When developing the new GMF, a spectrum specific to inland waters was used, taking into account the range of dimensionless fetches from 2000 to 20 000. The GMF proposed in this work was verified based on in situ wind speed measurements conducted in the southern part of Gorky Reservoir between 2017 and 2019 along with collocated images from Sentinel-1A, -1B SARs. It was shown that the accuracy of wind speed reconstruction based on the proposed GMF is higher than that obtained using the CMOD7 models and models developed for the Caspian Sea.
Keywords: SAR image, C-band, Sentinel-1, co-polarization, inland water body, geophysical model function, fetch, two-scale model
Full text

References:

  1. Baydakov G. A., Kandaurov A. A., Kuznetsova A. M., Sergeev D. A., Troitskaya Y. I., Field studies of features of wind waves at short fetches, Bull. of Russian Academy of Sciences: Physics, 2018, V. 82, No. 11, pp. 1431–1434.
  2. Girin S. N., Analysis of the validity of restrictions on the operation of passenger vessels in the Gorky reservoir, Russian J. Water Transport, 2022, No. 72, pp. 167–179 (in Russian), https://doi.org/10.37890/jwt.vi72.256.
  3. Karayev V. Yu., Balandina G. N., Modified wave spectrum and remote sensing, Issledovanie Zemli iz kosmosa, 2000, No. 5, pp. 1–12 (in Russian).
  4. Rusakov N. S., Sergeev D. A., Ermakova O. S. et al., Study of the applicability of C-band geophysical model function for SAR data in conditions of the Gorky Reservoir, Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, V. 21, No. 1, pp. 51–65 (in Russian), DOI: 10.21046/2070-7401-2024-21-1-51-65.
  5. Bass F. G., Fuks I. M., Kalmykov A. I. et al., Very high frequency radiowave scattering by a disturbed sea surface Part II: Scattering from an actual sea surface, IEEE Trans. on Antennas Propagation, 1968, V. 16, No. 5, pp. 560–568, DOI: 10.1109/TAP.1968.1139244.
  6. Elfouhaily T., Chapron B., Katsaros K., Vandemark D., A unified directional spectrum for long and short wind-driven waves, J. Geophysical Research: Oceans, 1997, V. 102, No. C7, pp. 15781–15796, http://dx.doi.org/10.1029/97jc00467.
  7. Fetterer F., Gineris D., Wackerman C. C., Validating a scatterometer wind algorithm for ERS-1 SAR, IEEE Trans. on Geoscience and Remote Sensing, 1998, V. 36, No. 2, pp. 479–492, DOI: 10.1109/36.662731.
  8. Hersbach H., Stoffelen A., de Haan S., An improved C-band scatterometer ocean geophysical model function: CMOD5, J. Geophysical Research: Oceans, 2007, V. 112, No. C3, Article C03006, https://doi.org/10.1029/2006JC003743.
  9. Hwang P. A., Wavenumber spectrum and mean square slope of intermediate-scale ocean surface waves, J. Geophysical Research: Oceans, 2005, V. 110, No. C10, Article C10029, https://doi.org/10.1029/2005JC003002.
  10. Katona T., Bartsch A., Estimation of wind speed over lakes in Central Europe using spaceborne C-band SAR, European J. Remote Sensing, 2018, V. 51, No. 1, pp. 921–931, https://doi.org/10.1080/22797254.2018.1516516.
  11. Klein L., Swift C., An improved model for the dielectric constant of sea water at microwave frequencies, IEEE Trans. on Antennas and Propagation, 1977, V. 25, No. 1, P. 104–111, https://doi.org/10.1109/TAP.1977.1141539.
  12. Komarov S., Komarov A., Zabeline V., Marine wind speed retrieval from RADARSAT-2 dual-polarization imagery, Canadian J. Remote Sensing, 2011, V. 37, No. 5, pp. 520–528, https://doi.org/10.5589/m11-063.
  13. Kudryavtsev V., Hauser D., Caudal G., Chapron B., A semiempirical model of the normalized radar cross-section of the sea surface 1. Background model, J. Geophysical Research: Oceans, 2003, V. 108, No. C3, pp. FET 2-1–FET 2-24, https://doi.org/10.1029/2001JC001003.
  14. McDaniel S. T., Small-slope predictions of microwave backscatter from the sea surface, Waves in Random Media, 2001, V. 11, No. 3, pp. 343–360, https://doi.org/10.1080/13616670109409789.
  15. Monaldo F. M., Jackson C., Li X., Pichel W. G., Preliminary evaluation of Sentinel-1A wind speed retrievals, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2016, V. 9, No. 6, pp. 2638–2642, https://doi.org/10.1109/JSTARS.2015.2504324.
  16. Li X.-M., Zhang T., Huang B., Jia T., Capabilities of Chinese Gaofen-3 synthetic aperture radar in selected topics for coastal and ocean observations, Remote Sensing, 2018, V. 10, No. 12, Article 1929, https://doi.org/10.3390/rs10121929.
  17. Lu Y., Zhang B., Perrie W. et al., A C-band geophysical model function for determining coastal wind speed using synthetic aperture radar, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2018, V. 11, No. 7, pp. 2417–2428, DOI: 10.1109/JSTARS.2018.2836661.
  18. Quilfen Y., Chapron B., Elfouhaily T. et al., Observation of tropical cyclones by high-resolution scatterometry, J. Geophysical Research: Oceans, 1998, V. 103, No. C4, pp. 7767–7786, https://doi.org/10.1029/97JC01911.
  19. Radkani N., Zakeri B. G., Southern Caspian Sea wind speed retrieval from C-band Sentinel-1A SAR images, Intern. J. Remote Sensing, 2020, V. 41, No. 9, pp. 3511–3534, https://doi.org/10.1080/01431161.2019.1706201.
  20. Ryabkova M., Karaev V., Guo J., Titchenko Yu., A review of wave spectrum models as applied to the problem of radar probing of the sea surface, J. Geophysical Research: Oceans, 2019, V. 124, No. 10, pp. 7104–7134, https://doi.org/10.1029/2018JC014804.
  21. Sergeev D., Ermakova O., Rusakov N. et al., Verification of C-band geophysical model function for wind speed retrieval in the open ocean and inland water conditions, Geosciences, 2023, V. 13, No. 12, Article 361, https://doi.org/10.3390/geosciences13120361.
  22. Stoffelen A., Anderson D., Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4, J. Geophysical Research: Oceans, 1997, V. 102, No. C3, pp. 5767–5780, https://doi.org/10.1029/96JC02860.
  23. Stoffelen A., Verspeek J. A., Vogelzang J., Verhoef A., The CMOD7 geophysical model function for ASCAT and ERS wind retrievals, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2017, V. 10, No. 5, pp. 2123–2134, https://doi.org/10.1109/JSTARS.2017.2681806.
  24. Voronovich A. G., Zavorotny V. U., Theoretical model for scattering of radar signals in Ku- and C-bands from a rough sea surface with breaking waves, Waves in Random Media, 2001, V. 11, No. 3, pp. 247–269, https://doi.org/10.1080/13616670109409784.
  25. Wright J., A new model for sea clutter, IEEE Trans. on Antennas Propagation, 1968, V. 16, No. 2, pp. 217–223, DOI: 10.1109/TAP.1968.1139147.
  26. Yang X., Li X., Zheng Q. et al., Comparison of ocean-surface winds retrieved from QuikSCAT scatterometer and Radarsat-1 SAR in offshore waters of the U. S. West Coast, IEEE Geoscience and Remote Sensing Letters, 2011, V. 8, No. 1, pp. 163–167, https://doi.org/10.1109/LGRS.2010.2053345.
  27. Zhang T., Li X.-M., Feng Q. et al., Retrieval of sea surface wind speeds from Gaofen-3 full polarimetric data, Remote Sensing, 2019, V. 11, No. 7, Article 813, https://doi.org/10.3390/rs11070813.
  28. Zhou L., Zheng G., Li X. et al., An improved local gradient method for sea surface wind direction retrieval from SAR imagery, Remote Sensing, 2017, V. 9, No. 7, Article 671, https://doi.org/10.3390/rs9070671.