Coseismic surface deformation of the 2014 Napa earthquake mapped by Sentinel-1A SAR and accuracy assessment with COSMO-SkyMed and GPS data as cross validation

ABSTRACT

The new land observation satellite Sentinel-1A was launched on 25 April 2014 with a C-band synthetic aperture radar (SAR) sensor, which has the significant enhancements in terms of revisit period and high resolution. The Mw 6.1 Napa, California earthquake occurring on 24 August 2014, almost 4 months after the launch, is the first moderate earthquake imaged by the Sentinel-1A. This provides an opportunity to map the coseismic deformation of the event and evaluate the potential of Sentinel-1A SAR for earthquake study. Two techniques including the interferometric SAR (InSAR) and pixel offset-tracking (PO) are, respectively, employed to map the surface deformation along the radar line of sight (LOS), azimuth and slant-range directions. The cross comparison between Sentinel-1A InSAR LOS deformation and GPS observations indicates good agreement with an accuracy of ～2.6?mm. We further estimate the earthquake source model with the external COSMO-SkyMed InSAR and GPS data as constraints, and forward calculate the surface deformation as cross validation with the Sentinel-1A observations. The comparison between the observed and modeled deformation shows that the Sentinel-1A measurement accuracy can achieve 1.6?cm for InSAR technique along LOS direction, and 6.3 and 6.7?cm for PO along azimuth and range directions, respectively.     

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.     

From ERS-1/2 to Sentinel-1: two decades of subsidence monitored through A-DInSAR techniques in the Ravenna area (Italy)

Land subsidence due to underground resources exploitation is a well-known problem that affects many cities in the world, especially the ones located along the coastal areas where the combined effect of subsidence and sea level rise increases the flooding risk. In this study, 25 years of land subsidence affecting the Municipality of Ravenna (Italy) are monitored using Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques. In particular, the exploitation of the new Sentinel-1A SAR data allowed us to extend the monitoring period till 2016, giving a better understanding of the temporal evolution of the phenomenon in the area. Two statistical approaches are applied to fully exploit the informative potential of the A-DInSAR results in a fast and systematic way. Thanks to the applied analyses, we described the behavior of the subsidence during the monitored period along with the relationship between the occurrence of the displacement and its main driving factors.     

利用Sentinel-1A数据监测地表形变案例分析

雷达卫星结合InSAR技术已广泛应用于高精度地表形变监测领域。本文选取2017年九寨沟地震为研究案例,利用Sentinel-1A地震前后的单视复数影像,基于D-InSAR技术获取该次地震的同震形变场。结果显示:震中西北侧表现出相对均匀的下沉现象,沉降漏斗区雷达视线向最大沉降量达25.1 cm;东南侧呈现不均匀抬升状态,地表破碎较为明显,最大抬升量为11.6 cm。研究表明基于Sentinel-1A数据的D-InSAR技术可以为地震形变场的定量分析提供一种快速有效的手段,为阐释地震发震机理及评估受灾情况提供必要的数据支撑,具有广阔的应用前景。     

利用Sentinel-1A数据监测南京河西地区地面沉降

南京河西地区是受长江和秦淮河淤积演化而成的漫滩地,由于河西新城大规模开发建设和地质条件的影响,地面沉降已成为该区域城市发展中不容忽视的问题。Sentinel-1数据是目前在轨运行的免费SAR数据,其具有较短的重访周期和较大的幅宽,为实现大范围长时序的地表形变监测提供了重要的数据源。利用短基线集干涉（SBAS-InSAR）技术对2015年4月至2018年4月覆盖南京河西地区的19景Sentinel-1A数据进行处理,获取了研究区2015—2018年间的地面沉降结果,并结合城市开发、人口分布等信息深入分析了地面沉降分布特征和成因。     

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.     

利用Sentinel-1A/1B雷达卫星数据监测南极接地线回退状况

南极接地线位置的准确确定对南极物质平衡计算、冰川动力学等具有重要意义。本文阐述了双差干涉测量（DDInSAR）提取接地线的基本原理,并利用欧空局Sentinel-1A/1B雷达卫星数据,基于双差干涉测量技术分别提取了东南极毛德皇后地沿岸冰架与西南极阿蒙森湾西侧Dotson冰架的接地线,将提取结果与已有接地线产品MEa-SUREs进行对比分析。结果表明,利用Sentinel-1A/1B雷达卫星数据,基于DDInSAR方法可对南极接地线进行提取及更新,并可对接地线的回退状况进行持续监测。通过监测,发现在Dotson冰架区域,接地线发生了较大的回退,1996—2018年的22年间,该区域的接地线大约回退2~5 km,其中最大回退距离达7.4 km。     

A method for monthly mapping of wet and dry snow using Sentinel-1 and MODIS: Application to a Himalayan river basin

Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km² river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk.