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, 2020, Vol. 17, No. 6, pp. 11-17

Calculated index of the compacting of sea ice cover from satellite images

A.I. Aleksanin 1 , M.G. Aleksanina 1 , A.Yu. Karnatsky 1 
1 Institute of Automation and Control Processes FEB RAS, Vladivostok, Russia
Accepted: 15.09.2020
DOI: 10.21046/2070-7401-2020-17-6-11-17
This paper describes a new method of automatic calculation of local indices of the compacting and divergence of sea ice cover. The proposed approach is based on the calculation of ice drift velocities. The local index of the compacting and divergence of sea ice cover is considered as the rate of change in the distance between individual elements of the sea ice cover. The local index of compacting and divergence is determined by two parameters: the scalar value of compacting/divergence and the direction of the axis of compacting/divergence. This approach allows the estimation of the accuracy and statistical significance of the calculated parameters. It was shown that the proposed approach results correspond to visually observed parameters of compacting and divergence.
Keywords: satellite images, ice drift, sea ice cover, compacting index, direction of compacting axis
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References:

  1. [1] Appolonov E. M., Sazonov K. E., Bokatova E. A., On the probability of sticking of vessels under ice pressure, The World of Transport, 2012, Vol. 10(4(42)), pp. 4–9.
  2. [2] Stepanyuk I. A., Smirnov V. N., Methods for measuring the characteristics of ice cover dynamics, Saint Petersburg: Gidrometeoizdat, 2001, 136 p.
  3. [3] Slivaev B. G., Preparation of the vessel for navigation in ice, Vladivostok: IPK MGU im. adm. G. I. Nevel’­skogo, 2017, 67 p.
  4. [4] Pyatkin V. P., Salov G. I., Statistical Approach to the Problem of Some Structures Detection in Aerospace Imagery, Science-intensive technologies, 2002, Vol. 3, No. 3, pp. 52–58.
  5. [5] Babich N. G., Selecting navigation routes and accessing efficiency of ice navigation data application, Earth from Space, 2011, No. 10, pp. 28–33.
  6. [6] Frolov S. V., Orientation of the leads and cracks in the ice cover relatively to direction of the ship movement is the most important characteristic of ice navigation in the arctic basin, Arctic and Antarctic Research, 2013, No. (97), pp. 35–45.
  7. [7] Gol’dshtein R. V., Osipenko N. M., Fracture mechanics and the problems of development of the Arctic, Arctic: Ecology and Economy, 2015, Vol. 4(20), pp. 14–27.
  8. [8] Yu J., Yang Y., Liu A., Zhao Y., Analysis of sea ice motion and deformation in the marginal ice zone of the Bering Sea using SAR data, Intern. J. Remote Sensing, 2009, Vol. 30(140), pp. 3603–3611.
  9. [9] Bouillon S., Rampal P., On producing sea ice deformation dataset from SAR-derived sea ice motion, The Cryosphere Discuss, 2014, Vol. 8, pp. 5105–5135.
  10. [10] Aleksanin A. I., Aleksanina M. G., Karnatskii A. Yu., Automatic computation of sea surface velocities on a sequence of satellite images, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2013, Vol. 10(2), pp. 131–142.
  11. [11] Emery W. J., Thomas A. C., Collins M. J., Crawford W. R., Mackas D. L., An objective method for computing advective surface velocities from sequential infrared satellite images, J. Geophysical Research, 1986, Vol. 91(C11), pp. 12865–12878.
  12. [12] Lavergne T., Eastwood S., Teffah Z., Schyberg H., Breivik L.-A., Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic, J. Geophysical Research, 2010, Vol. 115(C10), C10032, 14 p.