![]() ![]() The algorithm has been tested on seven icebergs, ranging in size from 54 sq km to 1052 sq km, roughly equivalent to the areas of the city of Bern in Switzerland and Hong Kong, respectively.Ī diverse dataset was compiled, incorporating between 15 and 46 images for each iceberg, spanning various seasons and the years 2014 –2020.Ī single Sentinel-1 image per month per iceberg was used to ensure dataset variety. Training ceases automatically when the system reaches its optimum performance, ensuring its adaptability and success on new examples. Throughout the training process, the system continually refines its predictions, adjusting its parameters based on the difference between the manually derived outline and the predicted result. It was meticulously trained using Sentinel-1 images exhibiting giant icebergs in various settings, with manually-derived outlines serving as the target. ![]() The architecture of the neural network is based on the renowned U-net design. The neural network introduced in this study is highly proficient in identifying the largest iceberg in each image, unlike comparative methods, which frequently select slightly smaller icebergs in proximity. ![]() To effectively track changes in iceberg area and thickness, essential for understanding how icebergs dissolve and release freshwater and nutrients into the ocean, pinpointing a specific giant iceberg for continuous monitoring is crucial. Its power lies in the neural networks' ability to understand intricate non-linear relationships and take the whole image context into account. The new neural network approach, however, excels in mapping iceberg extent even in these challenging conditions. “In addition, the Antarctic coastline may resemble icebergs in the satellite images, so standard segmentation algorithms often select the coast too instead of just the actual iceberg.” “Also, smaller iceberg fragments, which occur frequently near icebergs as they constantly lose bits of ice around their edges, are easily grouped together with the main iceberg by mistake. The same applies to wind-roughened ocean. Nevertheless, when the surroundings are complex, it can still sometimes be difficult to differentiate icebergs from sea ice or even the from the coastline.ĭr Braakmann-Folgmann, explained, “We have sometimes struggled to separate icebergs from surrounding sea ice that is rougher and older, and therefore looks brighter in the satellite images. Whereas in most radar images, as returned by Sentinel-1, icebergs appear as bright objects against the darker ocean and sea-ice background. ![]()
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