Integration of PSI, MAI, and Intensity-Based Sub-Pixel Offset Tracking Results for Landslide Monitoring with X-Band Corner Reflectors - Italian Alps (Corvara)
Integration of PSI, MAI, and Intensity-Based Sub-Pixel Offset Tracking Results for Landslide Monitoring with X-Band Corner Reflectors - Italian Alps (Corvara)
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DOI：
10.3390/rs10030409
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发表时间：
2018-03
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影响因子：
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通讯作者：
M. Darvishi;R. Schlögel;L. Bruzzone;G. Cuozzo
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文献类型：
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作者：
M. Darvishi;R. Schlögel;L. Bruzzone;G. Cuozzo
本文提出了一种集成干涉和强度偏移跟踪为基础的SAR遥感滑坡灾害减轻在意大利阿尔卑斯山的分析。尽管合成孔径雷达干涉测量（干涉合成孔径雷达）方法在量化滑坡变形方面具有优势，但仍存在一些局限性。时间去相关性、一维视线（LOS）观测限制、高速运动速率和多向运动特性使得植被覆盖区复杂滑坡难以准确监测。因此，互补和综合的方法，如偏移跟踪为基础的技术，需要克服这些干涉合成孔径雷达监测地表变形的限制。由于亚像素偏移跟踪对数据空间分辨率高度敏感，最新一代的合成孔径雷达传感器，如TerraSAR-X和COSMO-SkyMed，为更准确的危险评估开辟了有趣的前景。在本文中，我们认为高分辨率的X波段数据采集的COSMO-SkyMed（CSK）星座的永久散射体干涉测量（PSI），多孔径干涉测量（MAI）和偏移跟踪处理。我们分析了偏移跟踪技术，考虑区域和基于特征的匹配算法，以评估其适用性CSK数据，通过改进亚像素偏移估计。为此，PSI和MAI用于提取LOS和方位角位移分量。然后，四个著名的基于区域和五个基于特征的匹配算法（取自计算机视觉）应用于16个X波段角反射器。结果表明，偏移估计精度可以大大提高到小于3%的像素大小使用不同的基于特征的检测器和描述符的组合。这些技术的敏感性分析，适用于CSK数据，以监测复杂的滑坡在意大利阿尔卑斯山提供的优点和缺点，他们每个人的迹象。
This paper presents an analysis of the integration between interferometric and intensity-offset tracking-based SAR remote sensing for landslide hazard mitigation in the Italian Alps. Despite the advantages of Synthetic Aperture Radar Interferometry (InSAR) methods for quantifying landslide deformation, some limitations remain. The temporal decorrelation, the 1-D Line Of Sight (LOS) observation restriction, the high velocity rate and the multi-directional movement properties make it difficult to monitor accurately complex landslides in areas covered by vegetation. Therefore, complementary and integrated approaches, such as offset tracking-based techniques, are needed to overcome these InSAR limitations for monitoring ground surface deformations. As sub-pixel offset tracking is highly sensitive to data spatial resolution, the latest generations of SAR sensors, such as TerraSAR-X and COSMO-SkyMed, open interesting perspective for a more accurate hazard assessment. In this paper, we consider high-resolution X-band data acquired by the COSMO-SkyMed (CSK) constellation for Permanent Scatterers Interferometry (PSI), Multi-Aperture Interferometry (MAI) and offset tracking processing. We analyze the offset tracking techniques considering area and feature-based matching algorithms to evaluate their applicability to CSK data by improving sub-pixel offset estimations. To this end, PSI and MAI are used for extracting LOS and azimuthal displacement components. Then, four well-known area-based and five feature-based matching algorithms (taken from computer vision) are applied to 16 X-band corner reflectors. Results show that offset estimation accuracy can be considerably improved up to less than 3% of the pixel size using the combination of the different feature-based detectors and descriptors. A sensitivity analysis of these techniques applied to CSK data to monitor complex landslides in the Italian Alps provides indications on advantages and disadvantages of each of them.