基于SAR偏移量跟踪法提取岗纳楼冰川流速

冰川动态变化监测有助于反映全球和区域气候演变,保护自然环境和自然资源。近年来,基于SAR数据研究冰川运动已成为主流技术之一。基于SAR提取冰川流速主要包括合成孔径雷达干涉测量、多孔径雷达干涉和偏移量追踪法。本文采用SAR偏移量追踪法中的强度追踪法,提取青海省哈拉湖东北部岗纳楼冰川沿距离向、方位向的冰川流速。试验结果表明,距离向冰川运动速度提取效果较好,最大流速达15.36 m/a,流速从中轴向两侧递减,在冰舌末端趋于0;方位向提取的冰流速最大达18.27 m/a,但因电离层干扰,方位向流速图中存在一些方位向条纹。此外,由于冰流速在方位向分量小等因素的影响,本文研究提取的方位向流速精度低于距离向。     

岗纳楼冰川表面流速时空变化特征提取及分析

冰川表面流速是反映冰川动态变化的重要指标,能够为冰川物质平衡提供重要信息.利用2016年的13景Sentinel-1A影像和合成孔径雷达(synthetic aperture radar,SAR)偏移量追踪法测定岗纳楼冰川表面流速场,并根据地表温度是否大于0℃将其分为冰封期(10月—次年3月)和消融期(4月—9月).其...     

尼泊尔地震触发滑坡识别和雪崩形变分析

2015-04-25尼泊尔Gorkha附近发生了Mw 7.8级强震,引发尼泊尔及中国西藏地区大量的山体滑坡和雪崩灾害,造成了严重的人员伤亡与经济损失。基于Landsat 8影像和亚像素相关性匹配技术识别形变失相关区域,并结合目视解译提取震害滑坡与雪崩沉积区域,统计分析了所提取的滑坡数目、面积等与地形因子的关系,同时对珠峰雪崩高发区的冰川形变进行了定量分析。实验结果表明,提取形变场中的形变失相关区域并结合目视解译验证是一种识别震害滑坡与雪崩沉积区域的有效方法;统计结果显示滑坡体随坡度分布呈现高斯特性,多发生在坡度大于30°的地形,易发于河谷两侧,且高坡度更容易触发单体面积大的滑坡体。该研究为利用Landsat 8影像数据进行震害滑坡与雪崩沉积区域提取、雪崩高发区的冰川流速监测预警工作提供了新视角。     

阿尼玛卿冰川表面流速与地质灾害隐患点监测

为了更好地开展冰川变化与地质灾害隐患的监测研究,该文基于Sentinel-1A数据,使用合成孔径雷达影像偏移量追踪技术和GACOS辅助下的小基线集-InSAR方法,对阿尼玛卿冰川表面流速及周边区域地质灾害隐患点进行了监测分析。结果表明：2015—2021年阿尼玛卿冰川表面流速先增加后减缓,在2018年达到了最大(6 m/a);冰川流速暖季(5—9月)大于冷季(10月—次年4月);地质灾害隐患点多集中于冰川两侧,其形变速率与冰川运动速率一致性较好,推测与冰川融水对岩土体稳定性的影响有关。该文的研究结果可为冰川融化引起的地质灾害的防灾减灾工作提供重要参考。     

利用DInSAR的东南极极记录和达尔克冰川冰流速提取与分析

目的 利用1996年 ERS-1/2tandem SAR数据,采用 DInSAR方法提取了极记录和达尔克冰川的冰流速,并利用冰流速转换模型和该地区的实测值进行了对比。结果表明,DInSAR结果很好地体现了整个区域的冰流速。对于内陆地区,DInSAR提取的监测点冰流速和实测值非常吻合;对于达尔克冰川的前缘,受时间差异和潮汐等因素的影响,DInSAR推求的冰流速结果略小于实测值。     

利用InSAR数据的汶川地震形变场提取及分析

以2008年5月12日发生在中国四川的Mw 7.9级汶川地震为研究对象,由于汶川地震发生在植被覆盖茂密、地形起伏大的龙门山山区,常规的C波段雷达在这些区域几乎得不到任何有意义的信号,采用日本JAXA的L波段ALOS/PALSAR覆盖震区的震前和震后6个条带的卫星数据,以SRTM-DEM数据作为外部DEM,利用GAMMA软件进行二通差分干涉测量处理,获取了覆盖震区的同震形变场;并使用国家重大科学工程“中国地壳运动观测网络”项目组公布的震区GPS同震观测结果,与InSAR观测结果进行了比较分析,表明两者之间具有很好的一致性,通过传统差分干涉获取到的形变量精度可以达到cm级。     

2022年泸定Mw 6.6地震InSAR同震形变与滑动分布

2022-09-05,青藏高原东缘的鲜水河断裂上发生了泸定Mw 6.6地震,该地震是鲜水河断裂上40年来发生的最大地震,研究该地震的运动学和同震破裂模式对理解青藏高原东缘构造形变机制和评估鲜水河断裂以及安宁河断裂的地震危险性具有重要意义。利用Sentinel-1和ALOS-2卫星雷达影像,采用合成孔径雷达干涉技术获取了泸定地震的同震形变场,进而基于弹性半空间的位错模型,确定了本次地震发震断层的几何参数和滑动分布。结果表明,泸定地震是一次典型的左旋走滑事件,发震断层西倾,倾角约为72°,走向沿NNW-SSE方向,约为167°;断层破裂主要集中在0~10 km深度,最大滑动发生在约5.8 km深度,约为2.23 m;同震释放的地震矩约为8.74×1018 N·m,相当于矩震级Mw 6.59。通过对震后光学影像解译,发现此次地震诱发的滑坡多集中分布在发震断层西侧,该现象与余震主要集中在断层西侧的结果相一致,可认为是地震上盘效应的体现。     

DInSAR技术对地震同震形变场的研究

合成孔径雷达差分干涉测量（DInSAR）可用于监测厘米级或更微小的地表形变,以揭示许多物理现象,如地震形变、火山运动、大气变化、冰川漂移、地面沉降以及山体滑坡等。DInSAR作为一种新型的空间对地观测技术,具有不受时间和空间的限制、对地物具有一定的穿透性等传统测量所不可比拟的优势,已得到较为广泛的应用。简要介绍DInSAR技术的基本原理及其处理流程,以Barn地震为例提取Bam地震的同震形变场。     

DInSAR技术监测玉树地震同震形变场的研究

近二十年来,合成孔径雷达干涉测量技术（DInSAR）作为一种监测地表形变的有效技术得到广泛应用,其视线向精度可达厘米级甚至毫米级。该技术尤其是对监测快速、激烈的地表形变更为有效,如地震、火山等。利用DInSAR技术,选用日本ALOS卫星PALSAR数据,获取了2010—04—14玉树Mw6．9地震的同震形变场。结果表明：地表至少发生过3次地表破裂,沿断层走向的形变分布范围远远大于垂直断层分布范围,形变分布特征以左旋走滑为主。     

基于DInSAR技术监测地震形变及深度学习提取损毁建筑物 ——以厄瓜多尔为例

针对地震导致的地表变形、建筑物损坏等问题,利用合成孔径雷达差分干涉测量技术检测受灾区,并利用深度卷积网络提取损坏建筑物.以2016年4月16日厄瓜多尔地震为例,利用Sentinel-1A雷达数据获取地震形变.结果表明:厄瓜多尔地区整体地震形变在0～0.226 m,可检测形变变化为0.028 m;结合光学遥感影像进行分析...     

2015年尼泊尔Mw 7.8地震前OLR和电离层异常分析

针对2015-04-25尼泊尔Mw 7.8地震,利用NOAA卫星遥感射出长波辐射(OLR)数据和IGS(International GNSS Service)提供的全球IONEX总电子含量(TEC)数据,并考虑太阳和地磁活动水平的条件下,分别对OLR数据采用标准差阈值法和对电离层TEC数据采用四分位距法进行了异常探测。结果显示,2015-04-22在震中附近地区卫星遥感OLR出现异常增强现象;同时,2015-04-23在震中附近电离层TEC出现显著正异常现象,而且出现磁共轭现象。     

2015年尼泊尔地震Mw7.9产生的地球内部变形

针对地球内部变形的理论研究缺失,该文基于半无限空间的地球模型,研究了2015年尼泊尔地震Mw7.9产生的地球内部不同深处(地表以及地下10、20、30、50、100和300km)的同震位移变化,研究区域内的地表最大垂直位移有0.779 0m,向下的最大垂直位移是-0.383m,南北向的水平位移在断层处产生集中挤压,最大值有1.460 0m,这与尼泊尔境内的GPS观测结果比较吻合;地下10km处的位移比地表的变形要大很多;地球深部的位移结果逐渐变小,并且100km处的水平位移方向也发生了巨大变化。地球内部位移变化结果显示:地球浅部位移与地表的走向趋势一致但振幅不同,地表的位移并不是最大的,接近震源处的变形最大。     

尼泊尔Ms 8.1级地震活动构造及次生地质灾害研究

2015年尼泊尔Mw 7.8大地震诱发了大量的山体滑坡,对尼泊尔境内与周边地区造成了严重的影响。选取离震中较近的辛杜帕尔乔克地区作为研究区,基于L波段ALOS-2和C波段Sentinel-1A两种合成孔径雷达数据,采用堆叠合成孔径雷达干涉测量（interferometric synthetic aperture radar,InSAR）技术开展震后滑坡的探测与识别,结合光学影像圈定出滑坡隐患点14处。在此基础上,联合升降轨数据和多维小基线集（multidimensional small baseline subset,MSBAS)-InSAR技术获取了典型滑坡的二维时间序列形变特征,结果表明,该典型滑坡的主要形变发生在水平东西向,最大形变速率为-69 mm/a。同时,通过对该典型滑坡时间序列中的趋势项与周期项形变信号进行分析,发现地震对于滑坡运动具有明显的加速作用,且降雨量的增加使得滑坡位移在每年的8月-11月呈现出周期性变化,可为震后滑坡监测研究提供参考。

     

Subsidence in the Kathmandu Basin,before and after the 2015 Mw 7.8 Gorkha Earthquake,Nepal Revealed from Small Baseline Subset-DInSAR Analysis

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.     

利用InSAR及其差分技术获取仲巴地震的同震形变场

本文简要介绍了InSAR及其差分技术的基本原理,并以仲巴地震为例,采用已知DEM的二路差分法获取了仲巴地震的同震形变场。结果表明:仲巴地震为是一个以倾滑为主的浅源正断层型地震,断层面走向近乎南北方向。     

Estimating surface ice velocity on Chhota Shigri glacier from satellite data using Particle Image Velocimetry (PIV) technique

Information about the surface ice velocity is one of the important parameters for Mass balance and Glacier dynamics. This study estimates the surface ice velocity of Chhota Shigri glacier using Landsat (TM/ETM+) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) temporal data-sets from a period of 2009 to 2016 and 2006 to 2007, respectively. A correlation based Particle Image Velocimetry (PIV) technique has been used for the estimation of surface ice velocity. This technique uses multiple window sizes in the same data-set. Four window sizes (low, medium, high, very high) are used for each image pair. Estimated results have been compared with the published data. The outcomes attained from the medium window size closely matches with the published results. The estimated mean surface ice velocities of medium window size are 24 and 28.5 myr^?1 for 2009/2010 and 2006/2007 images pair. Highest velocity is observed in middle part of the glacier while lowest in the accumulation zone of the glacier.     

多视线向InSAR形变场约束的改则地震滑动分布反演

利用3种不同视线向LOS(Line Of Sight)的ENVISAT ASAR数据进行干涉处理,提取多视线向(Multi-LOS)的同震形变场;结合同震形变场特征与震源机制解,构建了改则地震双断层破裂模型;利用四叉树采样后的多视线向同震形变场进行约束,通过梯度下降法(Steepest Descent Method,SDM)与Crust2.0地壳分层模型反演了改则地震的同震滑动分布特征。结果表明:反演的形变残差得到有效控制,基本介于0±10 cm之间;主震断层的滑动量主要位于断层面2—16 km深部,最大滑动量可达1.34 m,位于断层面6.4 km深处;余震断层滑动量主要位于断层面2—6 km深部,最大滑动量可达0.90 m,位于断层面3.52 km深处;主震断层与余震断层均以正断为主,但主震断层还具有一定的左旋走滑分量,而余震断层的左旋走滑不明显;当剪切模量μ取3.2×1010Pa时,反演获得的主震与余震地震矩M0分别为6.34×1018N·M与1.20×1018N·M,分别相当于矩震级MW6.47与MW5.98。     

Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data

In 2019, four strong earthquakes of Mw>6.4 occurred successively in Mindanao, Philippines. Based on the reports from the USGS and PHIVOLCS, these earthquakes were dominated by strike-slip ruptures. Whether these earthquakes are temporally and spatially related remained unknown. We characterized the coseismic displacement fields during the earthquake sequence using an InSAR technique with Sentinel-1 SAR data. The InSAR deformation measurements convincingly reveal that the four earthquakes produced distinct coseismic displacement patterns. We estimated the source parameters of the earthquakes with a two-step inversion strategy. The optimal model suggests that the earthquake sequence resulted from the reactivation of a conjugate fault structure that involves two nearly vertical left-lateral strike-slip faults and two high-angle right-lateral strike-slip faults. We calculated Coulomb stress changes from the earthquake sequence, suggesting that the previous strong earthquakes had significant stress-encouraging effects on the following events. The regional velocities based on the GPS analysis suggest that the formation of this conjugate structure is mainly due to the westward movement of the subducting Philippine Sea Plate. This earthquake sequence provides a seismotectonic background for subsequent strong earthquakes and helps to better understand the formation mechanisms and seismotectonic implications of conjugate structure rupturing.     

A nonlinear inversion of InSAR-observed coseismic surface deformation for estimating variable fault dips in the 2008 Wenchuan earthquake

Satellite Interferometric Synthetic Aperture Radar (InSAR) is playing an increasingly important role in the observation of coseismic surface deformation caused by earthquakes, and has been used to invert for subsurface fault structure and reveal earthquake source mechanisms. However, the mapping of complex non-planar or curved (e.g., listric-shaped) faults still remains a challenging task due to variable dips along the underground depth and the impenetrability of the deep crust. Here, we develop a set of new inversion algorithms to determine the listric fault geometry with InSAR- and GPS-observed surface deformation as the significant constraints. The fault surface with variable dip angles is discretized into consecutive sub-fault layers along the down-dip direction. A nonlinear iteration algorithm is used to minimize the objective function to determine the dip angle for each sub-fault layer. The proposed method is first tested using synthetic data to show its effectiveness for retrieval of varying fault geometry dips, and then applied to the 2008 Mw 7.9 Wenchuan earthquake that ruptured the Yingxiu-Beichuan fault for over 320 km along the southwest-northeast strike. The inversion shows that the dip angle of the seismogenic fault is up to 76° near the surface layer, and gradually decreases along the down-dip direction. A significant decrease in dip occurs within the depths of 6–15 km with a dip of 32° at a depth of 15 km. The dip angle decreases to 2° at a depth of 20 km, and finally merges with the subparallel PengGuan fault, which is basically consistent with geological investigations and seismic waveform data inversion. Using the inferred fault geometry, the slip model associated with the event is estimated. Five high-slip concentrations along the strike of the Yingxiu-Beichuan fault are recognized. The inversion misfit of InSAR data is reduced to 7.1 cm with a significant improvement compared to previous studies.