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The Application of the Bursa Model to the Integration of GPS Time Series
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作者 Wang Ziyan Lin Shu +2 位作者 Wu Yanqiang Zhan Wei Ding Xiaoguang 《Earthquake Research in China》 2014年第1期46-53,共8页
In this paper the method of combining the Bursa model to integrate several regional time series to derive a unified global time series is introduced in detail. Then,an example taken from CMONOC( Crustal Movement Obser... In this paper the method of combining the Bursa model to integrate several regional time series to derive a unified global time series is introduced in detail. Then,an example taken from CMONOC( Crustal Movement Observation Network of China) is used to test if the combination method is feasible. The precision of the integrated time series with the combination method is below 2mm( North),3mm( East),that is same as the results from the direct integration of the time series and the precision of the baseline is below 6mm,which proves that the combination method can be used to integrate several regional time series to derive a unified global time series. 展开更多
关键词 gps time series INTEGRATION Bursa model
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Extraction of transient signal from GPS position time series by employing ICA
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作者 Shangwu Song Ming Hao +1 位作者 Yuhang Li Qingliang Wang 《Geodesy and Geodynamics》 EI CSCD 2023年第6期597-604,共8页
Transient deformation,such as post-seismic slip,slow slip and pre-seismic slip events,is a limited lowfrequency deformation that can last for hours to months,in contrast to a sudden slip on a fault caused by earthquak... Transient deformation,such as post-seismic slip,slow slip and pre-seismic slip events,is a limited lowfrequency deformation that can last for hours to months,in contrast to a sudden slip on a fault caused by earthquakes.Continuous Global Positioning System(CGPS),one of the most common geodetic techniques for continuously monitoring crustal deformation,is capable of capturing transient deformation signals.A critical point in characterizing transient deformation signals is the development of extracting and deciphering transient deformation signals from a huge and messy data set of position time series.Principal Component Analysis(PCA),one of the data-driven methods,has been employed to derive transient deformation signals from position time series combing with Kalman filtering.Independent Component Analysis(ICA)performs well in recovering and separating the sources of observed data,however,it is rarely used in extracting transient deformation signals.We aim to decompose the transient deformation signals from the daily GPS observation deployed in Akutan Island from 2007 to 2015 with the ICA method and obtain the spatiotemporal responses to the source signals of transient deformation.Our results indicate that ICA method can also characterize effectively transient deformation signals spatially and temporally.Additionally,the independent relationship between sources obtained by ICA allows for flexibility in linearly combining different sources. 展开更多
关键词 Transient deformation ICA Kalman filter gps time series Akutan
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Evaluation of micro-behavior of strain field in Chinese mainland with the GPS time se-ries
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作者 敬少群 王佳卫 +2 位作者 吴云 周硕愚 施顺英 《Acta Seismologica Sinica(English Edition)》 EI CSCD 2006年第5期514-521,共8页
Based on the time series of GPS station coordinate in the international Earth reference frame (ITRF), we evaluate annual micro-behavior of strain field in Chinese mainland with the triangle method. The results show ... Based on the time series of GPS station coordinate in the international Earth reference frame (ITRF), we evaluate annual micro-behavior of strain field in Chinese mainland with the triangle method. The results show that the annual micro-behavior of strain field is divided into two parts by the north-south earthquake belt in the research region. The prevailing direction of compressive principal strain field is nearly consistent in the western region. From west to east, the direction varies from NS to NE. It is in accordance with the direction of the modem compressive principal strain field. This suggests that geologic deformation in western region was mainly caused by that India tectonic plate pushes the research region northward and the Siberia plate pushes it southward relatively. It is an inheritance of new tectonic motion. The prevailing direction of the compressive principal strain field does not exist in the eastern region .The annual biggest shear strain is different greatly in every grid-cell. The values varies from 4.13×10^-8 to 7.0×10^-10. By and large the annual biggest shear strain in the western region is bigger than that in the eastern region. And so is the variation between any two consecutive biggest annual shear strains in the same grid-cell. The annual surface dilatation show that in most grid-cells of the research region the surface dilatation is in compressibility, and the variation between any two consecutive annual surface dilatation in the same grid-cell is small. 展开更多
关键词 gps time series micro-behavior of strain field annual strain field
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Co-seismic deformation for the 2015 M_(W)7.8 Gorkha earthquake(Nepal)using near-field GPS data
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作者 Jing Xiong Chao Chen +2 位作者 Jiaming Cao Junxiang Wang Xingbo Liu 《Geodesy and Geodynamics》 EI CSCD 2023年第5期419-430,共12页
Seasonal variations and common mode errors affect the precision of the Global Positioning System(GPS)time series.In this paper,we explore to improve the precision of coordinate time series,thereby providing a better d... Seasonal variations and common mode errors affect the precision of the Global Positioning System(GPS)time series.In this paper,we explore to improve the precision of coordinate time series,thereby providing a better detection of weak or transient deformation signals,particularly co-seismic signals.Based on 97 GPS stations,including the campaign and continuous GPS stations in Nepal and southern Tibet,we first consider seasonal variations and common errors,then obtain co-seismic deformation of the 2015 Gorkha earthquake in Nepal and southern Tibet.Our co-seismic rupture model is characterized by a shallow ramp and a deeper detachment fault,in agreement with the relocated aftershock sequence.Our results indicate that the earthquake rupture is mainly distributed in the upper-crustal fault,and the maximum slip is up to 8.0 m at~15.0 km depth located in the approximate-80 km east of the epicenter.The average slip is more than 5 m,and the total modelled magnitude is M_(W)7.84,consistent with the observed seismic moment.Our rupture model for the 2015 Gorkha earthquake suggests that the rupture zone is not only in the upper crustal Main Himalayan Thrust(MHT),but also spreads to the northern segment of the MHT. 展开更多
关键词 gps time series Co-seismic deformation Nepal earthquake
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Long aseismic slip duration of the 2006 Java tsunami earthquake based on GPS data
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作者 Rio Raharja Endra Gunawan +2 位作者 Irwan Meilano Hasanuddin Z.Abidin Joni Efendi 《Earthquake Science》 CSCD 2016年第5期291-298,共8页
The Java earthquake occurred on July 17, 2006 with magnitude 7.8 associated to the subduction process of Indo-Australian plate and Sundaland block off southwestern coast of Java. We present postseismic deformation par... The Java earthquake occurred on July 17, 2006 with magnitude 7.8 associated to the subduction process of Indo-Australian plate and Sundaland block off southwestern coast of Java. We present postseismic deformation parameters of the 2006 Java earthquake analyzed using campaign GPS observation from 2006 to 2008 and continuous observation from 2007 to 2014. We use an analytical approach of logarithmic and exponential functions to model these GPS data. We find that the decay time in the order of hundreds of days after the mainshock as observed by 8 years' data after the mainshock for magnitude 7 earthquake is longer than a general megathrust earthquake event. Our findings suggest that the 2006 Java earthquake which is considered as "tsunami earthquake" most probably occurred in the region that has low rigidity and tends to continuously slip for long time periods. 展开更多
关键词 2006 Java earthquake Aseismic slip gps time series
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Analysis of Abnormal Characteristics of Regional Crustal Deformation before the Menyuan MS6.4 Earthquake by GPS Continuous Data 被引量:2
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作者 Ma Haiping Feng Jiangang +1 位作者 Guo Peng Shi Xuelu 《Earthquake Research in China》 CSCD 2017年第2期234-238,共5页
In order to study the characteristics of crustal deformation around the epicenter before the 2016 M_S6. 4 Menyuan earthquake,the GPS continuous stations of the period from 2010 to 2016 were selected according to the o... In order to study the characteristics of crustal deformation around the epicenter before the 2016 M_S6. 4 Menyuan earthquake,the GPS continuous stations of the period from 2010 to 2016 were selected according to the observation data of the tectonic environment monitoring network in Chinese Mainland. The deformation characteristics of the crust before the earthquake were discussed through inter-station baseline time series analysis and the strain time series analysis in the epicentral region. The results show that a trend turn of the baseline movement state around the epicenter region occurred after 2014,and the movement after 2014 reflects an obvious decreasing trend of compressional deformation.During this period,the stress field energy was in a certain accumulation state. Since the beginning of 2014,the EW-component linear strain and surface strain rate weakened gradually before the earthquake. It shows that there was an obvious deformation deficit at the epicentral area in the past two years,which indicates that the region accumulated a high degree of strain energy before the earthquake. Therefore,there was a significant background change in the area before the earthquake. The results of the study can provide basic research data for understanding the seismogenic process and mechanism of this earthquake. 展开更多
关键词 Menyuan Ms6. 4 earthquake gps reference station Baseline time series Strain time series
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Preseismic deformation in the seismogenic zone of the Lushan MS7.0 earthquake detected by GPS observations 被引量:6
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作者 LIU XiaoXia WU YanQiang +4 位作者 JIANG ZaiSen ZHAN Wei LI Qiang WEI WenXin ZOU ZhenYu 《Science China Earth Sciences》 SCIE EI CAS CSCD 2015年第9期1592-1601,共10页
A continuous GPS array across the southern segment of the Longmenshan fault zone recorded the deformation during the process of the Lushan MS7.0 earthquake that occurred on April 20, 2013. Such data can provide meanin... A continuous GPS array across the southern segment of the Longmenshan fault zone recorded the deformation during the process of the Lushan MS7.0 earthquake that occurred on April 20, 2013. Such data can provide meaningful information regarding the dynamic evolution of crustal deformation in the seismogenic zone. Our studies have shown that the occurrence of the Wenchuan earthquake led to the loading of compressive and sinistral shearing strain on the southern segment of the Maoxian-Wenchuan fault, whereby the extrusion strain accumulated at a greater rate than before the Wenchuan earthquake. The strain time series in the seismogenic zone revealed that the principal compression strain rates decreased from west to east in the direction of N30°–45°W. Furthermore, the area to the east of Beichuan-Yingxiu fault behaved as a zone of compressive deformation with obvious sinistral shearing deformation. The surface strain and the first shearing strain time series decreased with time, while the area to the west of the Beichuan-Yingxiu fault behaved as a zone of dextral shear deformation that increased with time. Furthermore, the regional deformation field before the Lushan earthquake showed that the rate of extrusion strain accumulation in the southern segment of the Longmenshan fault zone was obviously larger than before the Wenchuan earthquake. Moreover, the sinistral shearing strain accumulated in the area of the southern segment of the Maoxian-Wenchuan fault. Based on the above analysis, we consider that the eastward movement of the Bayan Har block increased considerably following the Wenchuan earthquake, which enhanced the accumulation of compression strain in the southern segment of the Longmenshan fault zone. 展开更多
关键词 Lushan Ms7.0 earthquake gps observations gps baseline time series strain time series
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