Advertisement

An Introduction to Microwave Remote Sensing of the Asian Seas

  • Martin Gade
  • Ad Stoffelen
Chapter

Abstract

In this chapter passive and active microwave sensors are introduced, their basic measurement principles are described, and few examples of microwave (MW) remote sensing of the Asian Seas are given. The space-borne sensors under consideration are MW radiometer, altimeter, scatterometer, and synthetic aperture radar (SAR). It is demonstrated that changes in the sea surface roughness can be used to infer ocean surface vector wind fields, but also that this roughness may depend on other parameters such as SST, waves and currents.

Keywords

RADAR Microwaves Altimeter Radiometer Scatterometer SAR Bragg scattering Wind vector Normalized radar cross section 

Notes

Acknowledgements

Some of the authors’ views expressed in this chapter have been developed through discussions in a wide international forum, among which the International Ocean Vector Winds Science Team (IOVWST) and the International Winds Working Group (IWWG).

References

  1. Alpers W, Rufenach CL (1979) The effect of orbital motions on synthetic aperture radar imagery of ocean waves. IEEE Trans Antennas Propag 27:685–690CrossRefGoogle Scholar
  2. Alpers W, Hennings I (1984) A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar. J Geophys Res 89:10529–10546CrossRefGoogle Scholar
  3. Alpers W, Zhang B, Mouche A, Zeng K, Wai Chan P (2016) Rain footprints on C-band synthetic aperture radar images of the ocean—revisited. Remote Sens Environ 187:169–185CrossRefGoogle Scholar
  4. AVISO (2011) Aviso Users Newsletter. Online available at http://www.aviso.oceanobs.com. Accessed 03 Jan 2017
  5. Belmonte Rivas M, Stoffelen A, Verspeek J, Verhoef A, Neyt X, Anderson C (2017) Cone metrics: a new tool for the intercomparison of scatterometer records. IEEE J Sel Top Appl Earth Obs 10(5):2195–2204CrossRefGoogle Scholar
  6. Berger T (1972) Satellite altimetry using ocean backscatter. IEEE Trans Antennas Propag 20(3):295–309CrossRefGoogle Scholar
  7. Brekke C, Solberg AHS (2005) Oil spill detection by satellite remote sensing. Remote Sens Environ 95:1–13CrossRefGoogle Scholar
  8. Brusch S, Held P, Lehner S, Rosenthal W, Pleskachevsky A (2011) Underwater bottom topography in coastal areas from TerraSAR-X data. Int J Remote Sens 32:4527–4543CrossRefGoogle Scholar
  9. Fois F, Hoogeboom P, Le Chevalier F, Stoffelen A (2015) On the use of cross-polar scattering to observe very high winds. IEEE Trans Geosci Remote Sens.  https://doi.org/10.1109/TGRS.2015.2416203CrossRefGoogle Scholar
  10. Fois F, Hoogeboom P, Chevalier F, Stoffelen A, Mouche A (2016) DopSCAT: a mission concept for simultaneous measurements of marine winds and surface currents. J Geophys Res.  https://doi.org/10.1002/2015JC011011RRCrossRefGoogle Scholar
  11. Font J, Lagerloef GSE, Le Vine DM, Camps A, Zanife OZ (2004) The determination of surface salinity with the European SMOS space mission. IEEE Trans Geosci Remote Sens 42:2196–2205CrossRefGoogle Scholar
  12. Gade M, Alpers W, Hühnerfuss H, Masuko H, Kobayashi T (1998) The imaging of biogenic and anthropogenic surface films by a multi-frequency multi-polarization synthetic aperture radar measured during the SIR-C/X-SAR missions. J Geophys Res 103:18851–18866CrossRefGoogle Scholar
  13. Gade M, Byfield V, Ermakov S, Lavrova O, Mitnik L (2013) Slicks as indicators for marine processes. Oceanography 26(2):138–149CrossRefGoogle Scholar
  14. Gaiser PW, St. Germain KM, Twarog EM, Poe GA, Purdy W, Richardson D, Grossman W, Linwood Jones W, Spencer D, Golba G, Cleveland J, Choy L, Bevilacqua RM, Chang PS (2004) The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance. IEEE Trans Geosci Remote Sens 42(11): 2347CrossRefGoogle Scholar
  15. Goldstein RM, Zebker HA (1987) Interferometric radar measurement of ocean surface currents. Nature 328:707–709CrossRefGoogle Scholar
  16. Hersbach H, Stoffelen A, de Haan S (2007) An improved C-band scatterometer ocean geophysical model function: CMOD5. J Geophys Res 112(C3).  https://doi.org/10.1029/2006jc003743
  17. Holt B (2004) SAR imaging of the ocean surface. In: Jackson CR, Apel JR (eds) Synthetic aperture radar marine user’s manual. NOAA NESDIS Office of Research and Applications, Washington DC, pp 25–79Google Scholar
  18. Horstmann J, Koch W, Lehner S, Tonboe R (2000) Wind retrieval over the ocean using synthetic aperture radar with C band HH polarization. IEEE Trans Geosci Remote Sens 38:2122–2131CrossRefGoogle Scholar
  19. Johannessen JA, Chapron B, Collard F, Kudryavtsev K, Mouche A, Akimov D, Dagestad KF (2008) Direct ocean surface velocity measurements from space: improved quantitative interpretation of Envisat ASAR observations. Geophys Research Lett 35:L22608CrossRefGoogle Scholar
  20. Lin W, Portabella M,. Stoffelen A, Vogelzang J, Verhoef A (2015) ASCAT wind quality under high subcell wind variability conditions. J Geophys Res Oceans 120.  https://doi.org/10.1002/2015jc010861Google Scholar
  21. Lin W, Portabella M, Stoffelen A, Vogelzang J, Verhoef A (2016) On mesoscale analysis and ASCAT ambiguity removal. Q Meteorol Soc 142:1745–1756.  https://doi.org/10.1002/qj.2770CrossRefGoogle Scholar
  22. Melsheimer C, Gade M, Alpers W (1998) Investigation of multifrequency/multipolarization radar signatures of rain cells derived from SIR-C/X-SAR data. J Geophys Res 103:18867–18884CrossRefGoogle Scholar
  23. Mouche A, Collard F, Chapron B, Dagestad K-F, Guitton G, Johannessen J, Kerbaol V, Wergeland Hansen M (2012) On the use of doppler shift for sea surface wind retrieval from SAR. IEEE Trans Geosci Remote Sens 50(7):2901–2909CrossRefGoogle Scholar
  24. Portabella M, Stoffelen A (2004) A probabilistic approach for SeaWinds data assimilation. Q J R Meteorol Soc 130(596):127–152CrossRefGoogle Scholar
  25. Portabella M, Stoffelen A, Johannessen JA (2002) Toward an optimal inversion method for SAR wind retrieval. J Geophys Res 107(C8):1–13CrossRefGoogle Scholar
  26. Robinson IS (2010) Discovering the ocean from space. Springer, Heidelberg, p 638CrossRefGoogle Scholar
  27. Romeiser R (2014) Ocean applications of interferometric SAR. In: Njoku EG (ed) Encyclopedia of remote sensing. Springer, Heidelberg, pp 426–428CrossRefGoogle Scholar
  28. Skou N (2014) Microwave radiometers. In: Njoku EG (ed) Encyclopedia of remote sensing. Springer, Heidelberg, pp 382–385CrossRefGoogle Scholar
  29. Stoffelen A (1998) Scatterometry. Ph.D. thesis at the University of Utrecht. ISBN 90-393-1708-9Google Scholar
  30. Stoffelen A, Verspeek J, Vogelzang J, Verhoef A (2017) The CMOD7 geophysical model function for ASCAT and ERS wind retrievals. IEEE J Sel Top Appl Earth Obs 10(5):2123–2134CrossRefGoogle Scholar
  31. Tian-Kunze X, Kaleschke L, Maaß N, Mäkynen M, Serra N, Drusch M, Krumpen T (2013) SMOS derived sea ice thickness: algorithm baseline, product specifications and initial verification. Cryosphere Discuss 7:5735–5792CrossRefGoogle Scholar
  32. Ulaby FT, Moore RK, Fung AK (1981) Microwave remote sensing—active and passive, volume I: microwave remote sensing fundamentals and radiometry. Addison-Wesley, ReadingGoogle Scholar
  33. Van Zadelhoff GJ, Stoffelen A, Vachon PW, Wolfe J, Horstmann J, Belmonte-Rivas M (2014) Retrieving hurricane wind speeds using cross-polarization C-band measurements. Atmos Meas Tech 7:437–449CrossRefGoogle Scholar
  34. Vogelzang J, Stoffelen A (2017) ASCAT ultrahigh-resolution wind products on optimized grids. IEEE J Sel Top Appl Earth Obs 10(5):2332–2339CrossRefGoogle Scholar
  35. Wang Z, Stoffelen A, Zhao C, Vogelzang J, Verhoef A, Verspeek J, Lin M, Chen G (2017) An SST-dependent Ku-band geophysical model function for RapidScat. J Geophys Res Oceans 122:3461–3480CrossRefGoogle Scholar
  36. Wensink H, Campbell G (1997) Bathymetric map production using the ERS SAR. Backscatter 8:17–22Google Scholar
  37. Wentz FJ, Ricciardulli L, Gentemann C, Meissner T, Hilburn KA, Scott J (2013) Remote sensing systems Coriolis WindSat 3-day environmental suite on 0.25 deg grid, version 7.0.1, South East Asia. Remote sensing systems, Santa Rosa, CA. Available online at www.remss.com/missions/windsat. Accessed 03 Jan 2017
  38. Wright JW (1968) A new model for sea clutter. IEEE Trans Antennas Propag 16:217–223CrossRefGoogle Scholar
  39. Zavorotny VU, Gleason S, Cardellach E, Camps A (2014) Tutorial on remote sensing using GNSS bistatic radar of opportunity. IEEE Geosci Remote Sens Mag 2(4):8–45CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institut für Meereskunde, Universität HamburgHamburgGermany
  2. 2.Royal Netherlands Meteorological Institute (KNMI)De BiltThe Netherlands

Personalised recommendations