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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval
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The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval

机译：约束网络传播（C-NetP）技术可改善SBAS-DInSAR变形时间序列检索

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摘要

We present an innovative region-growing-based technique that permits to improve the surface displacement time-series retrieval capability of the two-scale Small BAseline Subset (SBAS) Differential Interferometric Synthetic Aperture Radar (DInSAR) approach in medium-to-low coherence regions. Starting from a sequence of multitemporal differential SAR interferograms, computed at the full spatial resolution scale, the developed method “propagates” the information on the deformation relevant to a set of high coherent SAR pixels [referred to as source pixels (SPs)], in correspondence to which SBAS-DInSAR deformation measurements have previously been estimated, to their less coherent neighbouring ones. In this framework, a minimum-norm constrained optimization problem, relying on the use of constrained Delaunay triangulations (CDTs), is solved, where the constraints represent the displacement values at the SP locations. Such DInSAR processing scheme, referred to as Constrained-Network Propagation (C-NetP), is easy to implement and, although specifically developed to work within the two-scale SBAS framework, it can be extended to wider DInSAR scenarios. The validity of the method has been investigated by processing a SAR dataset acquired over the city of Rome (Italy) by the Cosmo-SkyMed constellation from July 2010 to October 2012. The achieved results demonstrate that the proposed C-NetP method is capable to significantly increase the spatial density of the SBAS-DInSAR measurements, reaching an improvement of about 250%. Such an improvement allows revealing deformation patterns that are partially or completely hidden, by applying the conventional two-scale SBAS processing. This is particularly relevant in urban areas where the assessment and management of the risk associated to the deformation affecting infrastructures is strategic for decision makers and local authorities.
机译：我们提出了一种基于区域生长的创新技术，该技术可以提高中低相干区域中的两尺度小型BAseline子集（SBAS）差分干涉合成孔径雷达（DInSAR）方法的表面位移时间序列检索能力。从以全空间分辨率尺度计算的一系列多时相差分SAR干涉图开始，所开发的方法“传播”与一组高相干SAR像素[称为源像素（SP）]相关的变形信息。对应于先前估计的SBAS-DInSAR形变测量结果与相邻度较低的测量结果的对应关系。在此框架中，解决了依赖约束Delaunay三角剖分（CDT）的最小范数约束优化问题，其中约束表示SP位置的位移值。这种DInSAR处理方案称为约束网络传播（C-NetP），易于实施，尽管专门开发用于在两级SBAS框架内工作，但可以扩展到更广泛的DInSAR方案。通过处理2010年7月至2012年10月Cosmo-SkyMed星座在罗马市（意大利）获得的SAR数据集，研究了该方法的有效性。所得结果表明，所提出的C-NetP方法能够显着提高增加了SBAS-DInSAR测量的空间密度，提高了约250％。通过应用常规的两尺度SBAS处理，这样的改进允许揭示部分或完全隐藏的变形模式。这在城市地区尤为重要，因为在城市地区，与影响基础设施的变形相关的风险的评估和管理对于决策者和地方当局而言具有战略意义。

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