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Advances in polarimetric SAR interferometry and its application to geo/eco-environmental stress change monitoring

机译:极化SAR干涉测量技术的进展及其在地质/生态环境应力变化监测中的应用

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Radar polarimetry has established itself in high resolution POL-SAR imaging, image target characterization and selective image feature extraction. With the addition of single platform dual antenna interferometers, digital elevation mapping (DEM) was made possible (which can be recovered in most cases equally well from standard fully polarimetric POL-SAR image data utilizing the Schuler purely polarimetric DEM algorithms not requiring an interferometer). In order to be able to fully describe direction-sensitive environmental stress changes, it is necessary to rapidly advance repeat-pass (RP) fully polarimetric (POL: scattering matrix) differential (D) interferometric (In) SAR imaging systems (RP-POL-D-InSAR) which have emerged with the SIR-C/X-SAR Missions 1 and 2. In pursuing this goal, Cloude and Pottier (1997) introduced the polarimetric entropy/anisotropy method and Cloude and Papathanassiou (1997) introduced the polarimetric-interferometric phase coherence optimization (PIPCO) procedure. This PIPCO procedure is verified in this paper by utilizing an ideally matching repeat-pass pair of the SIR-C/X-SAR Mission 2, Tien-Shan tracks within the Russian Academy of Sciences, Siberian Division, Buriat Natural Science Center (RAS-SD-BNSC) SE Baikal Lake, Selenga Delta (Kabansk-Kudara-Oymur: 52.16/spl deg/ N, 106.67/spl deg/ E) Geo-environmental Sanctuary, the "Kudara Polygon" for which various institutes of RAS-SD-BNSC have collected extensive geographic (geo-ecological and geo- tectonic) environmental information and vegetative groundtruth data over several decades.
机译:雷达极化仪已在高分辨率POL-SAR成像,图像目标表征和选择性图像特征提取方面确立了自己的地位。通过添加单平台双天线干涉仪,使得数字高程映射(DEM)成为可能(在大多数情况下,可以使用不需要干涉仪的Schuler纯极化DEM算法从标准的全极化POL-SAR图像数据中很好地恢复) 。为了能够完全描述方向敏感的环境应力变化,有必要快速推进重复通过(RP)全极化(POL:散射矩阵)差分(D)干涉(In)SAR成像系统(RP-POL -D-InSAR)随SIR-C / X-SAR任务1和2出现。为实现这一目标,Cloude和Pottier(1997)介绍了极化熵/各向异性方法,Cloude和Papathanassiou(1997)介绍了极化方法。 -干涉相干优化(PIPCO)程序。本文利用SIR-C / X-SAR任务2的理想匹配重复通过对验证了该PIPCO程序,该对任务是俄罗斯科学院布里亚特自然科学中心西伯利亚分部(RAS- SD-BNSC)Selenga Delta SE贝加尔湖(Kabansk-Kudara-Oymur:52.16 / spl deg / N,106.67 / spl deg / E)地质环境保护区,RAS-SD- BNSC在过去的几十年中收集了广泛的地理(地质生态和大地构造)环境信息和植被真实数据。

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