Fuzzy clustering approach in unsupervised sea-ice classification

Fuzzy clustering approach for the determination of sea-ice types in polar regions from passive radar images is considered in this paper. The sea-ice concentration in polar regions is generally monitored by multichannel passive microwave imager, and the sea-ice types in polar regions are determined by clustering. However, the boundaries between different sea-ice types are often fuzzy and the results obtained by hard clustering algorithms are often not acceptable. In this paper, the fuzzy clustering algorithm is applied to segment arctic regions by sea-ice types. The number of clusters are determined by partition density method. The experimental results with daily observations for one-year period show that sea-ice types found by fuzzy clustering approach are stable. The formation and growth of sea-ice can also be monitored from the clustered results. (C) 1999 Elsevier Science B.V. All rights reserved.