A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

• Published in: Elementa: Science of the Anthropocene
• Main Authors: Hwang, Byongjun, Ren, Jinchang, McCormack, Samuel, Berry, Craig, Ayed, Ismail Ben, Graber, Hans C., Aptoula, Erchan
• Other Authors: Deming, Jody W., Lee, Craig M.
• Format: Article in Journal/Newspaper
• Language: English
• Published: University of California Press 2017
• Subjects: Sea ice
• Online Access: http://dx.doi.org/10.1525/elementa.154; http://online.ucpress.edu/elementa/article-pdf/doi/10.1525/elementa.154/473140/154-3386-2-pb.pdf

In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter) compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover.