Reconstructing movement history of frozen debris lobes in northern Alaska using satellite radar interferometry
Reconstructing movement history of frozen debris lobes in northern Alaska using satellite radar interferometry
复制标题
利用卫星雷达干涉测量法重建阿拉斯加北部冰冻碎片叶瓣的运动历史
DOI：
10.1016/j.rse.2018.12.014
复制
发表时间：
2019-02
影响因子：
13.5
通讯作者：
Daanen Ronald P
中科院分区：
文献类型：
--
作者：
Gong Wenyu;Darrow Margaret M;Meyer Franz J.;Daanen Ronald P
冻结碎片裂片（fdl）是沿永久冻土影响的斜坡缓慢移动的滑坡，由土壤、岩石、有机碎片和大量渗透冰区组成。基于它们与邻近基础设施的接近程度、大小和流动动力学，fdl代表着潜在的地质灾害。本文以美国阿拉斯加州布鲁克斯山脉道尔顿高速公路走廊内的8个fdl （FDL-A、-B、-C、-D、-4、-5、-7、-11）为研究对象。我们使用中分辨率合成孔径雷达（SAR）图像和差分SAR干涉测量（dInSAR）技术研究了FDL位移的时空变化。利用欧洲1/2遥感卫星（ERS /2）和相控阵型l波段合成孔径雷达（PALSAR）采集数据生成相干干涉图，研究了1995-1996年和2006-2010年fdl的位移历史。我们根据数据分辨率、季节和植被覆盖情况对卫星InSAR监测FDL运动的能力进行了初步评估，这也有助于我们选择有用的干涉图。通过多时间干涉位移图，我们发现7个被调查的fdl（由于数据覆盖范围有限，FDL-7被排除在这个子实验之外）在其移动模式上表现出强烈的空间和季节变化，最大位移率通常发生在10月，最小位移率通常发生在2月或3月，这与之前发表的实地研究结果一致。总的来说，通过本研究，我们：(1)利用包裹的PALSAR干涉图描绘了冬季的活动fdl；(2)分析了各FDL体内变形场的空间变异性；(3)通过多时相ERS串联干涉图分析模拟了FDL变形率的季节变化；(4)将insar导出的变形率与历史图像分析得到的变形率相结合，确定长期变形率。本研究的结果填补了历史图像分析中的空白，并提供了重要的季节和空间变形数据，这些数据对于制定缓解计划至关重要，因为这些特征接近基础设施。我们还总结了利用卫星雷达干涉测量技术研究这些运动特征的研究经验，相信这对未来类似特征的研究有用。
Frozen debris lobes (FDLs) are slow-moving landslides along permafrost-affected slopes, and consist of soil, rock, organic debris, and areas of massive infiltration ice. Based on their proximity to the adjacent infrastructure, their size, and their flow dynamics, FDLs represent potential geohazards. Eight FDLs (FDL-A, -B, -C, -D, -4, -5, -7, -11) within the Dalton Highway corridor in the Brooks Range, Alaska, USA are the subject of this paper. We examined temporal and spatial variation of FDL displacement using medium-resolution Synthetic Aperture Radar (SAR) images and differential SAR Interferometry (dInSAR) techniques. European Remote Sensing satellite 1/2 (ERS 1/2) and Phased Array type L-band Synthetic Aperture Radar (PALSAR) acquisitions were used to generate coherent interferograms to study the displacement history of FDLs for 1995–1996 and 2006–2010. We conducted an initial assessment of the capability of satellite InSAR to monitor FDL movement depending on data resolution, season, and vegetation coverage, which also helped us to select useful interferograms. With multi-temporal interferometric displacement maps, we found that seven investigated FDLs (FDL-7 was excluded from this sub-experiment due to limited data coverage) demonstrated strong spatial and seasonal variations in their movement patterns, with maximum displacement rates typically occurring in October and minimum displacement rates during February or March, which is consistent with previously published field study results. Overall, through this study we: (1) delineated the active FDLs during the winter period using a wrapped PALSAR interferogram; (2) analyzed the spatial variation of the deformation field within each FDL body; (3) modeled the seasonal changes of FDL deformation rates through the analysis of multi-temporal ERS tandem interferograms; and (4) integrated InSAR-derived deformation rates with those obtained through historical imagery analysis to determine long-term deformation rates. Results from this study fill the gaps left in the historical imagery analysis and provide important seasonal and spatial deformation data, which are essential in the development of a mitigation plan as these features approach infrastructure. We also summarize our research experience studying these moving features using satellite radar interferometry and believe this can be useful for future studies of similar features.
登录
查看更多内容
DOI：
10.1109/dfua.2003.1219956
发表时间：
2003-05
期刊：
2003 2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas
影响因子：
--
作者：
C. Colesanti;A. Ferretti;R. Locatelli;G. Savio
通讯作者：
C. Colesanti;A. Ferretti;R. Locatelli;G. Savio
DOI：
10.5194/tc-7-1109-2013
发表时间：
2013-07
期刊：
The Cryosphere
影响因子：
--
作者：
Lin Liu;C. Millar;R. Westfall;H. Zebker
通讯作者：
Lin Liu;C. Millar;R. Westfall;H. Zebker
DOI：
10.1109/tgrs.2002.803792
发表时间：
2002-11-01
影响因子：
8.2
作者：
Berardino, P;Fornaro, G;Sansosti, E
通讯作者：
Sansosti, E
影响因子：
8.2
作者：
Ferretti, A;Prati, C;Rocca, F
通讯作者：
Rocca, F
影响因子：
--
作者：
X. Tong;D. Sandwell;Y. Fialko
通讯作者：
X. Tong;D. Sandwell;Y. Fialko