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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Monitoring Glacier Changes Using Multitemporal Multipolarization SAR Images
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Monitoring Glacier Changes Using Multitemporal Multipolarization SAR Images

机译：使用多时相多极化SAR影像监测冰川变化

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This paper presents a processing chain for the change detection of Arctic glaciers from multitemporal multipolarization synthetic aperture radar (SAR) images. We produce terrain-corrected multilook complex covariance data by including the effects of topography on both geolocation and SAR radiometry as well as azimuth slope variations on polarization signature. An unsupervised contextual non-Gaussian clustering algorithm is employed for the segmentation of each terrain-corrected polarimetric SAR image and subsequently labeled with the aid of ground-truth data into glacier facies. We demonstrate the consistency of the segmentation algorithm by characterizing the expected random error level for different SAR acquisition conditions. This allows us to determine whether an observed variation is statistically significant and therefore can be used for the postclassification change detection of Arctic glaciers. Subsequently, the average classified images of succeeding years are compared, and changes are identified as the detected differences in the location of boundaries between glacier facies. In the current analysis, a series of dual-polarization C-band ENVISAT ASAR images over the Kongsvegen glacier, Svalbard, is used for demonstration.
机译：本文提出了一种用于从多时相多极化合成孔径雷达（SAR）图像中检测北极冰川变化的处理链。我们通过包括地形对地理位置和SAR辐射测量以及方位坡度变化对极化特征的影响，产生了地形校正的多视复方差数据。采用无监督的上下文非高斯聚类算法对每个经地形校正的极化SAR图像进行分割，然后借助地面真相数据将其标记为冰川相。我们通过表征不同SAR采集条件下的预期随机误差水平，证明了分割算法的一致性。这使我们能够确定观察到的变化是否具有统计学意义，因此可用于北极冰川的后分类变化检测。随后，将随后几年的平均分类图像进行比较，并将变化确定为检测到的冰川相边界位置的差异。在当前的分析中，以孔斯维根冰川斯瓦尔巴特群岛上的一系列双极化C波段ENVISAT ASAR图像为例。

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