SAR Imaging Features of Shallow Water Bathymetry

P. D. Pivaev1, ✉, V. N. Kudryavtsev1, 2, E. A. Balashova1, B. Chapron1, 3

1 Russian State Hydrometeorological University, Saint-Petersburg, Russian Federation

2 Marine Hydrophisical Institute of RAS, Sevastopol, Russian Federation

3 Institute Francais de Recherche pour I’Exploitation de la Mer, Plouzane, France

✉ e-mail: pivaev.pavel@gmail.com

Abstract

Purpose. The aim of the article is to study manifestations of the underwater topography features in the northern part of the White Sea in the images made by the spaceborn synthetic aperture radars (SAR) Sentinel-1A, Sentinel-1B.

Methods and Results. In the SAR images, the bottom features are revealed as bright and dark brightness anomalies. The anomalies were observed at the wind speed ranging from 2.6 to 10.8 m/s, and became reverse (bright anomalies turned dark and vice versa), when a tidal current changed its direction. It is shown that the observed SAR imagery contrasts correlate to divergence of a current formed by interaction of a tidal flow with the bottom topography inhomogeneities. The simulated SAR contrasts agree with the observations, and confirm the relation between the observed SAR contrasts and the current divergence. Together with modeling the SAR contrasts, the contribution of different mechanisms to formation of the observed modulations of the normalized radar cross section was qualitatively estimated. The wave breaking effect was especially accentuated. The method for retrieving the underwater bottom topography based on the relationship between the bottom gradient and the SAR imagery contrasts is proposed.

Conclusions. Location of the bottom inhomogeneities in the shallow water region on the whole coincides with that of the tidal current divergence and convergence zones, which are observed as brightness anomalies in the SAR images. Breaking of surface waves is the main contributor to the observed SAR contrasts. The bottom topography reconstructed from the SAR contrasts, and the actual one resulted from the bathymetry maps are in good agreement. Some discrepancies are interpreted as possible changes in depth and shape of the bottom topography features induced by action of strong currents and waves.

Keywords

bottom topography, Sentinel-1, SAR, wave breaking, current divergence

Acknowledgements

The work was carried out within the framework of project No. 17-77-30019 supported by Russian Scienсe Foundation; the authors are grateful to A.V. Zimin for providing the bottom topography data of the White Sea.

Original russian text

Original Russian Text © P. D. Pivaev, V. N. Kudryavtsev, E. A. Balashova, B. Chapron, 2020, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 36, Iss. 3, pp. 313-328 (2020)

For citation

Pivaev, P.D., Kudryavtsev, V.N., Balashova, E.A. and Chapron, B., 2020. SAR Imaging Features of Shallow Water Bathymetry. Physical Oceanography, 27(3), pp. 290-304. doi:10.22449/1573-160X-2020-3-290-304

DOI

10.22449/1573-160X-2020-3-290-304

References

  1. Jackson, C.R. and Apel, J.R., eds., 2004. Synthetic Aperture Radar Marine User’s Manual. Washington, DC: U.S. Department of Commerce, 464 p.
  2. Alpers, W. and Hennings, I., 1984. A Theory of the Imaging Mechanism of Underwater Bottom Topography by Real and Synthetic Aperture Radar. Journal of Geophysical Research: Oceans, 89(C6), pp. 10529-10546. https://doi.org/10.1029/JC089iC06p10529
  3. Shuchman, R.A., Lyzenga, D.R. and Meadows, G.A., 1985. Synthetic Aperture Radar Imaging of Ocean-Bottom Topography via Tidal-Current Interactions: Theory and Observations. International Journal of Remote Sensing, 6(7), pp. 1179-1200. doi:10.1080/01431168508948271
  4. Lodge, D.W.S., 1983. Surface Expressions of Bathymetry on Seasat Synthetic Aperture Radar Images. International Journal of Remote Sensing, 4(3), pp. 639-653. https://doi.org/10.1080/01431168308948580
  5. Romeiser, R. and Alpers, W., 1997. An Improved Composite Surface Model for the Radar Backscattering Cross Section of the Ocean Surface: 2. Model Response to Surface Roughness Variations and the Radar Imaging of Underwater Bottom Topography. Journal of Geophysical Research: Oceans, 102(C11), pp. 25251-25267. https://doi.org/10.1029/97JC00191
  6. Zheng, Q., Li, L., Guo, X., Ge, Y., Zhu, D. and Li, C., 2006. SAR Imaging and Hydrodynamic Analysis of Ocean Bottom Topographic Waves. Journal of Geophysical Research: Oceans, 111(C9), C09028. doi:10.1029/2006JC003586
  7. Calkoen, C.J., Hesselmans, G.H.F.M., Wensink, G.J. and Vogelzang, J., 2001. The Bathymetry Assessment System: Efficient Depth Mapping in Shallow Seas Using Radar Images. International Journal of Remote Sensing, 22(15), pp. 2973-2998. https://doi.org/10.1080/01431160116928
  8. Stewart, C., Renga, A., Gaffney, V. and Schiavon, G., 2016. Sentinel-1 Bathymetry for North Sea Palaeolandscape Analysis. International Journal of Remote Sensing, 37(3), pp. 471-491. doi:10.1080/01431161.2015.1129563
  9. Brusch, S., Held, P., Lehner, S., Rosenthal, W. and Pleskachevsky, A., 2011. Underwater Bottom Topography in Coastal Areas from TerraSAR-X Data. International Journal of Remote Sensing, 32(16), pp. 4527-4543. doi:10.1080/01431161.2010.489063
  10. Wackerman, C., Lyzenga, D., Ericson, E. and Walker, D., 1998. Estimating Near-Shore Bathymetry Using SAR. In: IEEE, 1998. IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing: Symposium Proceedings. Seattle, WA, USA: IEEE. Vol. 3, pp. 1668-1670. doi:10.1109/IGARSS.1998.692407
  11. Inglada, J. and Garello, R., 2002. On Rewriting the Imaging Mechanism of Underwater Bottom Topography by Synthetic Aperture Radar as a Volterra Series Expansion. IEEE Journal of Oceanic Engineering, 27(3), pp. 665-674. doi:10.1109/JOE.2002.1040949
  12. Caponi, E.A., Crawford, D.R., Yuen, H.C. and Saffman, P.G., 1988. Modulation of Radar Backscatter from the Ocean by a Variable Surface Current. Journal of Geophysical Research: Oceans, 93(C10), pp. 12249-12263. doi:10.1029/JC093iC10p12249
  13. Kudryavtsev, V., Akimov, D., Johannessen, J. and Chapron, B., 2005. On Radar Imaging of Current Features: 1. Model and Comparison with Observations. Journal of Geophysical Research: Oceans, 110(C7), C07016. doi:10.1029/2004JC002505
  14. Kudryavtsev, V.N., Fan, S., Zhang, B., Mouche, A.A. and Chapron, B., 2019. On Quad-Polarized SAR Measurements of the Ocean Surface. IEEE Transactions on Geoscience and Remote Sensing, 57(11), pp. 8362-8370. doi:10.1109/TGRS.2019.2920750
  15. Fan, S., Kudryavtsev, V., Zhang, B., Perrie, W., Chapron, B., Mouche, A., 2019. On C-Band Quad-Polarized Synthetic Aperture Radar Properties of Ocean Surface Currents. Remote Sensing, 11(19), 2321. https://doi.org/10.3390/rs11192321
  16. Lee, J.-S., Grunes, M.R. and Mango, S.A., 1991. Speckle Reduction in Multipolarization, Multifrequency SAR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 29(4), pp. 535-544. doi:10.1109/36.135815
  17. De Loor, G.P., 1978. Remote Sensing of the Sea by Radar. Analysis of Available Data and Results of Noordwijk '77. Hague, Netherlands: Physics LAB RVO-TNO, 59 p.
  18. De Loor, G.P., 1981. The Observation of Tidal Patterns, Currents and Bathymetry with SLAR Imagery of the Sea. IEEE Journal of Oceanic Engineering, 6(4), pp. 124-129. doi:10.1109/JOE.1981.1145501

Download the article (PDF)