Identification of Extreme Ice Features in the Canadian Arctic

I. Zakharov, P. Bobby, S. Warren, D. Power
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Abstract

Research on automatic detecting, tracking and characterizing extreme ice features in the Arctic is based on analyzing and processing satellite synthetic aperture radar (SAR) and optical images. Algorithms to identify ridges from very high-resolution optical data have an accuracy of 86.4% when compared to manual extraction and ridge height has been estimated from shadow. SAR signatures of various ice features have been analyzed and the results indicate that it is possible to identify rubble fields from other ice types.
加拿大北极地区极端冰特征的识别
基于卫星合成孔径雷达(SAR)和光学图像的分析与处理,研究了北极极端冰特征的自动探测、跟踪与表征。与人工提取相比,从高分辨率光学数据中识别山脊的算法的准确率为86.4%,并且山脊高度已从阴影中估计出来。分析了各种冰的SAR特征,结果表明可以从其他冰类型中识别碎石场。
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