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Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method

机译:全极化SAR偏移跟踪方法监测滑坡位移

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Landslide monitoring is important for geological disaster prevention, where Synthetic Aperture Radar (SAR) images have been widely used. Compared with the Interferometric SAR (InSAR) technique, intensity-based offset tracking methods (e.g., Normalized Cross-Correlation method) can overcome the limitation of InSAR’s maximum detectable displacement. The normalized cross-correlation (NCC) method, based on single-channel SAR images, estimates azimuth and range displacement by using statistical correlation between the matching windows of two SAR images. However, the matching windows—especially for the boundary area of landslide—always contain pixels with different moving characteristics, affecting the precision of displacement estimation. Based on the advantages of polarimetric scattering properties, this paper proposes a fully polarimetric SAR (PolSAR) offset tracking method for improvement of the precision of landslide displacement estimation. The proposed method uses the normalized inner product (NIP) of the two temporal PolSAR Pauli scattering vectors to evaluate their similarity, then retrieve the surface displacement of the Slumgullion landslide located in southwestern Colorado, USA. A pair of L-band fully polarimetric SAR images acquired by the Jet Propulsion Laboratory’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected for experiment. The results show that the Slumgullion landslide’s moving velocity during the monitoring time ranges between 1.6–10.9 mm/d, with an average velocity of 6.3 mm/d. Compared with the classical NCC method, results of the proposed method present better performance in the sub-pixel estimation. Furthermore, it performs better when estimating displacement in the area around the landslide boundaries.
机译:滑坡监测对于预防地质灾害非常重要,其中合成孔径雷达(SAR)图像已被广泛使用。与干涉式SAR(InSAR)技术相比,基于强度的偏移跟踪方法(例如归一化互相关方法)可以克服InSAR最大可检测位移的局限性。基于单通道SAR图像的归一化互相关(NCC)方法通过使用两个SAR图像的匹配窗口之间的统计相关性来估计方位角和范围位移。但是,匹配窗口(尤其是滑坡的边界区域)始终包含具有不同运动特性的像素,从而影响位移估算的精度。基于极化散射特性的优势,提出一种完全极化SAR(PolSAR)偏移跟踪方法,以提高滑坡位移估计的精度。所提出的方法使用两个时间PolSAR Pauli散射矢量的归一化内积(NIP)来评估它们的相似性,然后获取位于美国西南科罗拉多的Slumgullion滑坡的表面位移。实验选择了由喷气推进实验室的无人飞行器合成孔径雷达(UAVSAR)系统获取的一对L波段全极化SAR图像。结果表明,在监测时间内,Slumgullion滑坡的移动速度为1.6-10.9 mm / d,平均速度为6.3 mm / d。与经典的NCC方法相比,该方法的结果在子像素估计中表现出更好的性能。此外,在估算滑坡边界周围区域的位移时,它的效果更好。

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