Applicability of Fuzzy Clustering for the Identification of Upwelling Areas on Sea Surface Temperature Images
نویسندگان
چکیده
This work explores the applicability of fuzzy clustering methods to the segmentation of sea surface temperature (SST) images for the automatic identification of upwelling areas in the coastal ocean of Portugal. This has been done by exploring the fuzzy c-means algorithm. Visualization of fuzzy c-partitions is achieved by means of color mapping. Selection of the best c-partition that represents the upwelling stages is done using the XieBeni validation index. Besides, by measuring the matching rate between a c-partition and ‘ground truth’ image whose upwelling area had been manually contoured by oceanographers, one evaluates how closely the algorithm reproduces the shape of the upwelling areas.
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