Climate change is a cause of the expansion of snowmelt phenomena in the Antarctic, and shifts in position of wet and dry snow lines have been considered as good indicators of climate changes. The impacts of climate change are observable by the delineation of significant position change of glacier zones. The principal limitation of current glacier zone classification methods by synthetic aperture radar (SAR) image is that it is difficult to discriminate dry-snow and wet-snow zones using only single-polarimetric radar backscattering intensity. This study tried to solve the problem using polarimetric SAR (PolSAR). Analysis indicates that polarimetric decomposition elements could be efficient characteristics to delineate radar glacier zones by recognition of principal backscatter patterns. Further, two radar glacier zone classification processes for polarimetric SAR are proposed: a supervised support vector machine (SVM) classification process and a simple decision-tree classification method. These methods enable reliable delineation of radar glacier zones in the Antarctic Peninsula. Polarimetric SAR, which provides more information about the scattering processes and target structure, proves to be an efficient tool for delineating radar glacier zones and snowmelt detection.

中文翻译：

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使用极化SAR划定南极半岛的雷达冰川区

气候变化是南极融雪现象扩大的一个原因，干湿雪线位置的变化被认为是气候变化的良好指标。气候变化的影响可以通过冰川区域显着位置变化的划分来观察。当前通过合成孔径雷达 (SAR) 图像进行冰川区分类的主要局限性在于，仅使用单极化雷达后向散射强度难以区分干雪区和湿雪区。本研究试图使用极化 SAR (PolSAR) 解决该问题。分析表明，极化分解元素可能是通过识别主要反向散射模式来划定雷达冰川区的有效特征。更多，提出了两种极化SAR的雷达冰川带分类方法：监督支持向量机（SVM）分类方法和简单的决策树分类方法。这些方法能够可靠地描绘南极半岛的雷达冰川区。极化 SAR 可提供有关散射过程和目标结构的更多信息，被证明是用于描绘雷达冰川区和融雪探测的有效工具。