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Landfast sea ice monitoring using multisensor fusion in the Antarctic

机译：利用多传感器融合在南极进行陆上快速海冰监测

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摘要

Landfast sea ice (fast ice) means sea ice that is attached to the shoreline with little or no motion in contrast to pack ice which drifts on the sea. As fast ice plays an important role in the environmental and biological systems of the Antarctic, it is crucial to accurately monitor the spatiotemporal distribution of fast ice. Previous studies on fast ice using satellite remote sensing were mostly focused on the Arctic and near-Arctic areas, whereas few studies were conducted over the Antarctic, especially the West Antarctic region. This research mapped fast ice using multisensor data from 2003 to 2008 based on machine learning approaches - decision trees (DTs) and random forest (RF). A total of seven satellite-derived products, including Advanced Microwave Scanning Radiometer for the Earth observing system brightness temperatures and sea ice concentration, Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) and Special Sensor Microwave/Imager ice velocity, were used as input variables for identifying fast ice. RF resulted in better performance than that of DT for fast ice classification. Visual comparison of the fast ice classification results with 250-m MODIS images for selected areas also revealed that RF outperformed DT. Ice velocity and IST were identified as the most contributing variables to classify fast ice. Spatiotemporal variations of fast ice in the East and West Antarctic were also examined using the time series of the fast ice maps produced by RF. The residence time of fast ice was much shorter in the West Antarctic than in the East.
机译：陆上海冰（快冰）是指附着在海岸线上的海冰很少或没有运动，而浮冰则在海上漂流。由于速冻冰在南极的环境和生物系统中起着重要作用，因此准确监测速冻冰的时空分布至关重要。先前使用卫星遥感进行的速冻研究主要集中在北极和近北极地区，而在南极，特别是西南极地区进行的研究很少。这项研究基于机器学习方法-决策树（DT）和随机森林（RF），使用2003年至2008年的多传感器数据绘制了快速冰图。总共使用了七个卫星衍生产品，包括用于地球观测系统亮度温度和海冰浓度的高级微波扫描辐射仪，中分辨率成像光谱仪（MODIS）的冰面温度（IST）和特殊传感器微波/成像仪的冰速。作为识别快速冰的输入变量。对于快速冰分类，RF的性能优于DT。快速冰分类结果与选定区域的250米MODIS图像的视觉比较还表明，RF优于DT。冰速和IST被认为是对快速冰进行分类的最主要变量。还使用RF产生的快速冰图的时间序列，检查了南极东部和西部快速冰的时空变化。在南极西部，快速冰的停留时间比东部要短得多。

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  • 来源
    《GIScience & remote sensing》 |2015年第2期|239-256|共18页
  • 作者

    Kim Miae; Im Jungho; Han Hyangsun; Kim Jinwoo; Lee Sanggyun; Shin Minso; Kim Hyun-Cheol;

  • 作者单位

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea|LIG Nex1 Co Ltd, Space Imaging R&D Lab, Yongin, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea;

    Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan, South Korea;

    Korea Polar Res Inst, Div Polar Ocean Environm, Inchon, South Korea;

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  • 正文语种 eng
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  • 关键词

    decision trees; landfast sea ice; Antarctic; random forest;

    机译：决策树;陆地海冰;南极洲;随机森林;

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