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Borehole-GPR numerical simulation of full wave field based on convolutional perfect matched layer boundary

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Journal of Central South University 2013年第3期20卷 764-769页

作者：朱自强彭凌星鲁光银密士文 school of geosciences and info-physics Central South University

The absorbing boundary is the key in numerical simulation of borehole *** match layer(PML) was chosen as the absorbing boundary in numerical simulation of *** CPML(convolutional perfect match layer) approach that we have chosen has the advantage of being media *** with the Maxwell equations in a two-dimensional structure,numerical formulas of finite-difference time-domain(FDTD) method with CPML boundary condition for transverse electric(TE) or transverse magnetic(TM) wave are presented in ***,there are three models for borehole-GPR *** analyzing the simulation results,the features of targets in GPR are obtained,which can provide a better interpretation of real radar *** results show that CPML is well suited for the simulation of borehole-GPR.

关键词： borehole-GPR numerical simulation convolutional perfect match layer finite-difference time-domain method

Introducing atmospheric angular momentum into prediction of length of day change by generalized regression neural network model

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Journal of Central South University 2014年第4期21卷 1396-1401页

作者：王琪洁杜亚男刘建 school of geosciences and info-physics Central South University

The general regression neural network(GRNN) model was proposed to model and predict the length of day(LOD) change, which has very complicated time-varying characteristics. Meanwhile, considering that the axial atmospheric angular momentum(AAM) function is tightly correlated with the LOD changes, it was introduced into the GRNN prediction model to further improve the accuracy of prediction. Experiments with the observational data of LOD changes show that the prediction accuracy of the GRNN model is 6.1% higher than that of BP network, and after introducing AAM function, the improvement of prediction accuracy further increases to 14.7%. The results show that the GRNN with AAM function is an effective prediction method for LOD changes.

关键词： general regression neural network(GRNN) length of day atmospheric angular momentum(AAM) function prediction

A landscape shape index-based sampling approach for land cover accuracy assessment

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Science China Earth Sciences 2016年第12期59卷 2263-2274页

作者： CHEN Fei CHEN Jun WU Hao HOU DongYang ZHANG WeiWei ZHANG Jun ZHOU XiaoGuang CHEN LiJun school of geosciences and info-physics Central South University National Geomatics Center of China

Spatial sampling design is one of the key steps in land cover accuracy assessment,and many traditional sampling approaches may not achieve credible spatial sampling due to the high spatial heterogeneity of land *** paper characterizes the spatial heterogeneity with three-level LSIs and determines the subsequent sample sizes and their spatial *** three-level LSIs are rLSI in a region,cLSI for each land cover class and uLSI in each geographic sampling unit in the *** rLSIs are used to derive appropriate sample sizes in the target *** cLSIs are used to assure that larger sample numbers are allocated to land cover classes with higher spatial *** uLSIs provide useful measures for selecting optimal geographic units in which sample sites will be *** LSI-based sampling approach can derive the sample sizes and determine their distributions in an adaptive way according to the spatial *** experimental case study further demonstrates that the LSI-based sampling approach obtains more appropriate sample sizes for each region,sufficient sample numbers for rare classes,and optimal sample distributions in the geographical space.

关键词： Land cover Sampling Landscape index Spatial heterogeneity Accuracy assessment

Regularized inversion for coseismic slip distribution with active constraint balancing

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Journal of Central South University 2017年第12期24卷 2961-2968页

作者： TONG Xiao-zhong XIE Wei GAO Da-wei school of geosciences and info-physics Central South University school of Earth and Ocean Sciences University of Victoria

Estimating the spatial distribution of coseismic slip is an ill-posed inverse problem, and solutions may be extremely oscillatory due to measurement errors without any constraints on the coseismic slip distribution. In order to obtain stable solution for coseismic slip inversion, regularization method with smoothness-constrained was imposed. Trade-off parameter in regularized inversion, which balances the minimization of the data misfit and model roughness, should be a critical procedure to achieve both resolution and stability. Then, the active constraint balancing approach is adopted, in which the trade-off parameter is regarded as a spatial variable at each model parameter and automatically determined via the model resolution matrix and the spread function. Numerical experiments for a synthetical model indicate that regularized inversion using active constraint balancing approach can provides stable inversion results and have low sensitivity to the knowledge of the exact character of the Gaussian noise. Regularized inversion combined with active constraint balancing approach is conducted on the 2005 Nias earthquake. The released moment based on the estimated coseismic slip distribution is 9.91×1021 N·m, which is equivalent to a moment magnitude of 8.6 and almost identical to the value determined by USGS. The inversion results for synthetic coseismic uniform-slip model and the 2005 earthquake show that smoothness-constrained regularized inversion method combined with active constraint balancing approach is effective, and can be reasonable to reconstruct coseismic slip distribution on fault.

关键词： coseismic slip inversion trade-off parameter active constraint balancing model resolution matrix spread function

Monitoring landslide associated with reservoir impoundment using synthetic aperture radar interferometry: A case study of the Yalong reservoir

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Geodesy and Geodynamics 2022年第2期13卷 138-150页

作者： Zhe Liu Bing Xu Qijie Wang Wenyan Yu Zelang Miao school of geosciences and info-physics Central South UniversityChangsha 410083China

The construction of large reservoirs can address the problem of uneven distribution of rivers in time and space,thereby meeting the needs of human production and ***,the huge elevation of the water level in some areas may modify the distribution of the groundwater level,causing geological disasters,such as surface deformation and *** Yalong reservoir supplies water to the downstream area of Shannan,Tibet;however,since the reservoir started storing water in 2017,the government has discovered two ancient *** this study,to monitor the deformation of the Yalong reservoir since its construction in 2014,we first used synthetic aperture radar(SAR) data and the multidimensional small baseline subset(MSBAS) method to obtain the deformation in the east-west and vertical *** result indicated the presence of three large,slow-moving landslides:Landslides I and II,located on the right bank of the Yalong reservoir,which are consistent with the results obtained by the actual survey,and a new discovery,Landslide Ⅲ,located on the left side of the ***,the experimental results indicated that the dam had undergone obvious deformation after impoundment,which should not be *** global positioning system and interferometric SAR(InSAR) timeseries deformation residual data were used to verify the accuracy of the InSAR *** results also showed that the deformation caused by the three landslides had te nded to accele rate after the rese rvoir’s impoundment,and that the failure mode was retrogressive *** found that InSAR plays a vital role in landslide detection and failure mode research around reservoirs,and assists in providing early warning for subsequent landslide disasters.

关键词： Landslide monitoring Two-dimensional deformation Yalong reservoir SBAS-InSAR

Solar cycle prediction using a long short-term memory deep learning model

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Research in Astronomy and Astrophysics 2021年第1期21卷 119-126页

作者： Qi-Jie Wang Jia-Chen Li Liang-Qi Guo school of geosciences and info-physics Central South UniversityChangsha 410083China

In this paper,we propose a long short-term memory(LSTM)deep learning model to deal with the smoothed monthly sunspot number(SSN),aiming to address the problem whereby the prediction results of the existing sunspot prediction methods are not uniform and have large *** method optimizes the number of hidden nodes and batch sizes of the LSTM network structures to 19 and 20,*** best length of time series and the value of the timesteps were then determined for the network training,and one-step and multi-step predictions for Cycle 22 to Cycle 24 were made using the well-established *** results showed that the maximum root-mean-square error(RMSE)of the one-step prediction model was6.12 and the minimum was only *** maximum amplitude prediction error of the multi-step prediction was 17.2%and the minimum was only 3.0%.Finally,the next solar cycles(Cycle 25)peak amplitude was predicted to occur around 2023,with a peak value of about *** accuracy of this prediction method is better than that of the other commonly used methods,and the method has high applicability.

关键词： Sun:solar activity Sun:sunspot number techniques:deep learning techniques:long short-term memory

Review of the SBAS InSAR Time-series algorithms, applications, and challenges

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Geodesy and Geodynamics 2022年第2期13卷 114-126页

作者： Shaowei Li Wenbin Xu Zhiwei Li school of geosciences and info-physics Central South UniversityChangsha 410083China

In the past 30 years,the small baseline subset(SBAS)InSAR time-series technique has emerged as an essential tool for measuring slow surface displacement and estimating geophysical *** of its ability to monitor large-scale deformation with millimeter accuracy,the SBAS method has been widely used in various geodetic fields,such as ground subsidence,landslides,and seismic *** obtained long-term time-series cumulative deformation is vital for studying the deformation *** article reviews the algorithms,applications,and challenges of the SBAS ***,we recall the fundamental principle and analyze the shortcomings of the traditional SBAS algorithm,which provides a basic framework for the following improved time series ***,we classify the current improved SBAS techniques from different perspectives:solving the ill-posed equation,increasing the density of high-coherence points,improving the accuracy of monitoring deformation and measuring the multi-dimensional ***,we summarize the application of the SBAS method in monitoring ground subsidence,permafrost degradation,glacier movement,volcanic activity,landslides,and seismic ***,we discuss the difficulties faced by the SBAS method and explore its future development direction.

关键词： InSAR Small baseline subset Time-series InSAR Deformation

Coseismic slip distribution of 2009 L'Aquila earthquake derived from InSAR and GPS data

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Journal of Central South University 2012年第1期19卷 244-251页

作者： WANG Yong-zhe ZHU Jian-jun OU Zi-qiang LI Zhi-wei XING Xue-min school of geosciences and info-physics Central South UniversityChangsha 410083China

To better understand the mechanism of the Mw6.3 L＇Aquila （Central Italy） earthquake occurred in 2009, global positioning system （GPS） and interferometric synthetic aperture radar （InSAR） data were used to derive the coseismic slip distribution of the earthquake fault. Firstly, based on the homogeneous elastic half-space model, the fault geometric parameters were solved by the genetic algorithm. The best fitting model shows that the fault is a 13.7 km×14.1 km rectangular fault, in 139.3° strike direction and 50.2° southwest-dipping. Secondly, fixing the optimal fault geometric parameters, the fault plane was extended and discretized into 16× 16 patches, each with a size of 1 kmx 1 krn, and the non-uniform slip distribution of the fault was inverted by the steepest descent method with an appropriate smoothing ratio based on the layered crustal structure model. The preferred solution shows that the fault is mainly a normal fault with slight right-lateral strike slip, the maximum slip of 1.01 m is located in the depth of 8.28 km, the average rake is -100.9°, and the total geodetic moment is about 3.34× 1018 N.m （Mw 6.28）. The results are much closer than previous studies in comparison with the seismological estimation. These demonstrate that the coseismic fault slip distribution of the L＇Aauila earthauake inverted by the crustal model considering layered characters is reliable.

关键词： L'Aquila earthquake interferometric synthetic aperture radar global positioning system (GPS) slip distribution

Mitigation of time-series InSAR turbulent atmospheric phase noise: A review

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Geodesy and Geodynamics 2022年第2期13卷 93-103页

作者： Zhiwei Li Meng Duan Yunmeng Cao Minzheng Mu Xin He Jianchao Wei school of geosciences and info-physics Central South UniversityChangsha 410083HunanChina

Synthetic Aperture Radar(SAR)interferometry is one of the most powerful remote sensing tools for ground deformation ***,tropospheric delay greatly limits the measurement accuracy of the InSAR *** vertically stratified tropospheric delays have been extensively investigated and well tackled,turbulent tropospheric phase noise still remains an intractable *** recent years,great efforts have been made to reduce the influence of turbulent atmospheric *** contribution is intended to provide a systematic review of the progress achieved in this ***,it introduces the physical characteristics of atmospheric signals in ***,a review of the main mitigation algorithms proposed in the literature is *** addition,the strengths and weaknesses of each approach are analyzed to provide guidance for choosing a suitable method ***,sug-gestions for resolving the challenging issues and an outlook for future research are given.

关键词： InSAR Turbulent atmospheric phase Variance and covariance matrix Stochastic model Deep learning