Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files

An object-based method for automatic iceberg detection from Advanced Synthetic Aperture Radar (ASAR) images has been developed and applied in the Amundsen Sea, Antarctica. The automatic identification is based on brightness and spatial parameters of the ASAR images at five scale levels, and was verified with manual classification in four areas chosen to represent varying environmental conditions. The presented algorithm works comparatively well with images of the ocean in freezing temperatures and strong wind conditions, common in the Amundsen Sea. The detection rate was 96.2% which corresponds to 93.2% of the icebergs area, for all seasons. The algorithm generated 3.8% errors in the form of 'misses' and 7.0% of 'false alarms', mainly caused by the presence of ice floes. The method was applied on 432 radar images acquired in 2011 under different meteorological, oceanographic and sea ice conditions. As an output a map showing the probability of finding icebergs has been created. It shows that high probability coincides with depth contours and indicates a westward drift of the bergs throughout the whole region.本研究开发了一种面向对象的冰山自动检测方法，可从高级合成孔径雷达（Advanced Synthetic Aperture Radar，ASAR）图像中提取冰山信息，并将该方法应用于南极洲阿蒙森海海域。该自动识别流程基于五个尺度层级下ASAR图像的亮度与空间参数构建，并通过选取代表不同环境条件的四个区域开展人工分类验证。所提出的算法在阿蒙森海常见的低温强风海洋图像场景中表现优异。全季节场景下，该方法的检测率达96.2%，对应的冰山面积覆盖比例为93.2%；算法产生的漏检（misses）误差与误报（false alarms）误差分别为3.8%与7.0%，此类误差主要由浮冰的存在引发。 本方法共应用于2011年获取的432幅雷达图像，涵盖了不同气象、海洋学与海冰条件。最终生成了一张标注冰山发现概率的专题地图，该地图显示高概率区域与等深线分布重合，同时揭示了研究区域内冰山整体向西漂移的运动趋势。