Spatio-Temporal Coherence Based Technique for Near-Real Time Sea-Ice Identification from Scatterometer Data


The identification of sea-ice has frequently been cited as one of the most important tasks for deriving the sea-ice parameters and to avoid erroneous retrieval of wind vector over sea-ice infested oceans using space-borne scatterometer data. Discrimination between sea-ice and ocean is ambiguous under the high wind and/or thin/scattered ice conditions. The pre-launch technique developed for Oceansat-2, utilizes the dual-polarized QuikSCAT scatterometer data by using the spatio-temporal coherence properties of sea ice in addition to backscatter coefficient and the Active Polarization Ratio. Results were compared with the operational sea-ice products from National Snow and Ice Data Center. The threshold API value of −0.025 was found optimum for sea-ice and ocean discrimination. The overall sea-ice identification accuracy achieved was of the order of 95 per cent, ranging from 92.5% (during December in Southern Hemisphere) to 98% (during March in Northern Hemisphere). The applicability of the algorithm for both the Arctic as well as Antarctic makes it suitable for its operational use with the Oceansat-2 scatterometer data.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3


  1. Abreu, R., De Wilson, K., Arkett, M., & Langlois, D. (2002). Evaluating the use of QuikSCAT data for operational sea-ice monitoring. Proc. IGARSS, June 2002, Canada.

  2. Comiso, J. C. (2003). Large scale characteristics and variability of the global sea ice cover. In D. N. Thomas & G. S. Dickmann (Eds.), Sea ice—an introduction to its physics, chemistry, biology and geology (pp. 112–142). Malden: Blackwell Publishing.

    Google Scholar 

  3. Haarpaintner, J., Tonboe, R. T., & Long, D. G. (2004). Automatic detection and validity of the sea-ice edge: an application of enhanced-resolution QuikSCAT/Sea winds data. IEEE Transactions on Geoscience and Remote Sensing, 42, 1433–1443.

    Article  Google Scholar 

  4. Maslanik, J., & Stroeve, J. (1999). Updated daily, Near real-time DMSP SSM/I daily polar gridded sea-ice concentrations, 01 March to 31 December, 2007. Boulder Colorado USA: National Snow and Ice Data Center. Digital Media.

    Google Scholar 

  5. Remund, Q. P., & Long, D. G. (1999). Sea ice extent mapping using Ku-band Scatterometer data. Journal of Geophysical Research, 104(C5), 11515–11527.

    Article  Google Scholar 

  6. Stroeve, J., & Meier, W. (1999). Sea-ice trends and climatologies from SMMR and SSM/I, 1978–2002. Boulder, Colorado, USA: National Snow and Ice Data Center. Digital Media. (updated 2007).

  7. Tonboe, R., & Ezraty, R. (2002). Monitoring of new-ice in Greenland waters. Proc. IGARSS, Toronto, ON, Canada, June 2002, pp. 1932–1934.

  8. Ulaby, F. T., Moore, R. K., & Fung, A. K. (1986). Radar measurements of sea-ice. In: Microwave Remote Sensing, Vol. 3, Artech House, Norwood, 1986. Chap. 20-4.

  9. Vyas, N. K., Dash, M. K., Bhandari, S. M., Khare, N., Mitra, A., & Pandey, P. C. (2003). On the secular trend in sea-ice extent over the Antarctic region based on OCEANSAT—1 MSMR observations. International Journal of Remote Sensing, 24, 2277–2287.

    Article  Google Scholar 

  10. Yueh, S. H., Kwok, R., Lou, S. H., & Tsai, W. Y. (1997). Sea ice identification using dual-polarized Ku-band Scatterometer data. IEEE Transactions on Geoscience and Remote Sensing, 35, 560–569.

    Article  Google Scholar 

Download references


Authors gratefully acknowledge the suggestions and encouragement provided by R R Navalgund, Director, Space Applications Centre (SAC) and JS Parihar, Deputy Director, EPSA/SAC. The suggestions of M. Chakraborty and P K Pal (SAC) have made the article more meaningful. QuikSCAT sigma-0 data are obtained from the NASA sponsored Scatterometer Climate Record Pathfinder at Brigham Young University through the courtesy of David G Long (

Author information



Corresponding author

Correspondence to Sandip R. Oza.

About this article

Cite this article

Oza, S.R., Singh, R.K.K., Vyas, N.K. et al. Spatio-Temporal Coherence Based Technique for Near-Real Time Sea-Ice Identification from Scatterometer Data. J Indian Soc Remote Sens 39, 147–152 (2011).

Download citation


  • Sea-Ice identification
  • Scatterometer
  • QuikSCAT
  • Spatio-temporal coherence