We propose an algorithm for ice crack identification and detection using u-net network, which can realize the automatic detection of Antarctic ice cracks. Based on the data of sentinel-1 EW from January to February every year, in order to suppress the speckle noise of SAR image, the probabilistic patch based weights (ppb) algorithm is selected for filtering, and then representative samples are selected and input into the u-net network for model training, and the ice cracks are predicted according to the trained model. Taking five typical ice shelves（Amery、Fimbul、Nickerson、Shackleton、Thwaiters) in Antarctica as an example, the average accuracy of classification results can reach 94.5%, of which the local accuracy of fissure area can reach 78.6%, and the recall rate is 89.4%.
LI Xinwu , LIANG Shuang , YANG Bojin , ZHAO Jingjing
In order to better understand the mechanism of the interaction between the global climate and the Fimbu and Jelbart ice shelves, it is important to obtain the long-term ice velocity changes in this region. 1960-1980s Ice Flow Velocity Field Data Product Set of the Fimbul and Jelbart Ice Shelves, East Antarctica: Using the early Argon, Landsat MSS and TM satellite images, based on pre-processing the early remote sensing images to obtain the orthophoto images with precise geometric status, a layered matching method under the constraint strategy of artificial point feature point grid point was proposed, and the historical ice flow velocity field data product of the Fimbul Jelbart Ice Shelf, East Antarctica was extracted. This study is of great significance for studying the historical ice velocity of the Fimbul Jelbart Ice Shelf in East Antarctica from 1963 to 1987, and can provide basic data for studying the response of the ice sheet to global climate change.
LI Rongxing , FENG Tiantian , LI Yanjun , CHENG Yuan , QIAO Gang
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