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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 living.However,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 landslides.The 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 landslides.In 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 directions.The 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 reservoir.Meanwhile,the experimental results indicated that the dam had undergone obvious deformation after impoundment,which should not be ignored.The global positioning system and interferometric SAR(InSAR) timeseries deformation residual data were used to verify the accuracy of the InSAR method.The 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 landslide.We 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

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 detection.However,tropospheric delay greatly limits the measurement accuracy of the InSAR technique.While vertically stratified tropospheric delays have been extensively investigated and well tackled,turbulent tropospheric phase noise still remains an intractable issue.In recent years,great efforts have been made to reduce the influence of turbulent atmospheric delay.This contribution is intended to provide a systematic review of the progress achieved in this field.First,it introduces the physical characteristics of atmospheric signals in interferograms.Then,a review of the main mitigation algorithms proposed in the literature is provided.In addition,the strengths and weaknesses of each approach are analyzed to provide guidance for choosing a suitable method accordingly.Finally,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

Inversion of vegetation height from Pol In SAR using complex least squares adjustment method

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Science China Earth Sciences 2015年第6期58卷 1018-1031页

作者： FU HaiQiang WANG ChangCheng ZHU JianJun XIE QingHua ZHAO Rong School of Geosciences and Info-Physics Central South University

In this paper, we propose the novel method of complex least squares adjustment(CLSA) to invert vegetation height accurately using single-baseline polarimetric synthetic aperture radar interferometry(Pol In SAR) data. CLSA basically estimates both volume-only coherence and ground phase directly without assuming that the ground-to-volume amplitude radio of a particular polarization channel(e.g., HV) is less than ?10 d B, as in the three-stage method. In addition, CLSA can effectively limit errors in interferometric complex coherence, which may translate directly into erroneous ground-phase and volume-only coherence estimations. The proposed CLSA method is validated with Bio SAR2008 P-band E-SAR and L-band SIR-C Pol In SAR data. Its results are then compared with those of the traditional three-stage method and with external data. It implies that the CLSA method is much more robust than the three-stage method.

关键词：最小二乘法植被高度合成孔径雷达干涉测量调整反演 SIR-C SAR数据直接转化

InSAR林下地形测绘方法:理论、进展、挑战与前景

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Journal of Central South University 2020年第4期27卷 997-1011页

作者：谢雁洲朱建军付海强汪长城 School of Geosciences and Info-Physics Central South UniversityChangsha 410083China

近几十年来,森林覆盖区林下地形的重要意义与应用已得到广泛认可,许多学者对此开展了大量高精度林下地形绘图的研究。然而,森林场景的高时空动态性使得传统的测量技术难以重建精确的林下地形。微波遥感为林下地形测绘带来了契机,其能在... 详细信息

近几十年来,森林覆盖区林下地形的重要意义与应用已得到广泛认可,许多学者对此开展了大量高精度林下地形绘图的研究。然而,森林场景的高时空动态性使得传统的测量技术难以重建精确的林下地形。微波遥感为林下地形测绘带来了契机,其能在有限的时间内大范围提取、重建林下地形,其中包括合成孔径雷达干涉测量(InSAR),极化合成孔径雷达干涉测量(PolInSAR)和层析SAR(TomoSAR)。本文首先介绍了基于InSAR生成数字高程模型(DEM)的主要原理以及森林区域SAR数据的获取。随后,综合分析了基于InSAR,PolInSAR和TomoSAR的林下地形提取方法,并讨论其相关的应用及反演性能。最后,重点介绍了未来高精度林下地形测绘所面临的四个方面的挑战,包括SAR数据采集,误差补偿和校正,散射模型重建与解译以及多源数据融合的解决方案与策略。

关键词：林下地形微波遥感干涉SAR 极化干涉SAR 层析SAR

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中南大学地球科学进展与前沿

Journal of Central South University 2020年第4期27卷 975-996页

作者：郭振威赖健清张可能毛先成王智琳郭荣文邓浩孙平贺张绍和于淼崔益安柳建新 School of Geosciences and Info-Physics Central South UniversityChangsha 410083China

中南大学地质资源与地质工程一级学科自主创立了国际领先的地洼学说、伪随机多频电磁场理论及广域电磁勘探系统,在壳体大地构造学、地电场勘探理论与装置系统、多因复成成矿理论、三维成矿预测、复杂地层钻井技术等领域形成了具有国际... 详细信息

中南大学地质资源与地质工程一级学科自主创立了国际领先的地洼学说、伪随机多频电磁场理论及广域电磁勘探系统,在壳体大地构造学、地电场勘探理论与装置系统、多因复成成矿理论、三维成矿预测、复杂地层钻井技术等领域形成了具有国际影响的中南学派。2000年以来,伪随机电磁法勘探系统和广域电磁法勘探系统在国内外开展了广泛的推广应用,其中'均匀广谱伪随机电磁法及其应用'于2006年获得国家技术发明二等奖、'大深度高精度广域电磁勘探技术与装备'于2018年获得国家技术发明一等奖。本学科是危机矿山深边部接替资源勘探、地质和地球物理有机结合并直接服务于国民经济主战场的国家级重点学科。20年来,本学科以创立的成矿与找矿理论为指导,以自主研制的国家领先的电磁勘探系统为手段,在国内外矿山和成矿区带的深边部资源勘探中大显身手,在国内外众多矿山找到了一大批矿产资源,缓解了大批矿山的资源危机,取得了巨大的经济社会效益。本学科还在复杂地层钻进技术与极端地层钻具研制理论与技术、地质灾害监测与防治、三维可视化定位定量预测等方面的成果在国内享有盛誉。

关键词：地球物理地质学地球化学地质工程

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 deviations.Our method optimizes the number of hidden nodes and batch sizes of the LSTM network structures to 19 and 20,respectively.The 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 network.The results showed that the maximum root-mean-square error(RMSE)of the one-step prediction model was6.12 and the minimum was only 2.45.The 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 114.3.The 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

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 cover.This paper characterizes the spatial heterogeneity with three-level LSIs and determines the subsequent sample sizes and their spatial distributions.The three-level LSIs are rLSI in a region,cLSI for each land cover class and uLSI in each geographic sampling unit in the region.The rLSIs are used to derive appropriate sample sizes in the target regions.The cLSIs are used to assure that larger sample numbers are allocated to land cover classes with higher spatial heterogeneity.The uLSIs provide useful measures for selecting optimal geographic units in which sample sites will be located.This LSI-based sampling approach can derive the sample sizes and determine their distributions in an adaptive way according to the spatial heterogeneity.An 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

Research on GNSS deformation monitoring based on multi-baseline solution

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Research on GNSS deformation monitoring based on multi-basel...

Space-associated domain adaptation for three-dimensional mineral prospectivity modeling

第十三届中国卫星导航年会

作者： Haonan Wang Wujiao Dai Wenkun Yu School of Geosciences and Info-Physics Central South University

The existing GNSS deformation monitoring systems often adopt the single-baseline solution（SBS） model due to its simplicity and ease of implementation. When monitoring long-span linear objects such as bridges and railways, or large-area land subsidence, multiple reference stations are often used. However, the SBS model neglects the mathematical correlation between baselines, and sometimes the accuracy and reliability can be limited due to long baseline length and satellite occlusion. This paper proposes to use the multi-baseline solution（MBS） model to solve the deformation monitoring network. Based on real monitoring datasets, the accuracy of MBS model and SBS model were compared. The experimental results show that, compared with SBS, MBS can improve the ambiguity fixing rate and the coordinate accuracy by up to 22.7% and 27.8% respectively.

关键词： Multi-baseline solution Multiple reference stations Deformation monitoring GNSS

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International Journal of Digital Earth 2023年第1期16卷 2885-2911页

作者： Yang Zheng Hao Deng Jingjie Wu Ruisheng Wang Zhankun Liu Lixin Wu Xiancheng Mao Jing Chen School of Geosciences and Info-Physics Central South UniversityChangsh1People’s Republic of China Department of Geomatics Engineering University of CalgaryCalgaryCanada

Geographical information systems(GIS)are essential tools for mineral prospectivity modeling(MPM).Three-dimensional(3D)MPM is able to learn the association between geological evidence and mineralization in shallow zones and thereby build a prospectivity model for deep zones,making it a desirable technique to target deep-seated orebodies.However,existing 3D MPM methods directly generalize the model learned in shallow zones to the deep zones without attention to model transferability caused by the different metallogenic mechanisms between the two zones.In this study,we aim to robustly transfer the prospectivity model learned from shallow zones to deep zones.We cast the 3D MPM as a domain adaptation problem,which is an important realm of transfer learning.Because the metallogenic mechanism can be closely associated with spatial locations,we specifically focus on domain adaption concerning the spatial locations that are ignored by conventional domain adaptation methods.To measure the spatial-associated domain discrepancy,we propose a novel spatial-associated maximum mean discrepancy(SAMMD),which compares the joint distributions of features and spatial locations across domains.Based on the SAMMD criterion,a deep neural network,referred to as the spatial-associated domain adaptation network,is devised to learn cross-domain but mineralization-indicative features for building prospectivity model that is transferable to deep zones.A case study of the world-class Sanshandao gold deposit,in eastern China,was carried out to validate the effectiveness of the proposed methods.The results show that compared with other leading MPM methods and other domain adaption variants,the proposed method has superior prediction accuracy and targeting efficiency,demonstrating the effectiveness and robustness of the proposed method in targeting deep-seated orebodies in areas with different metallogenic mechanisms and no labeled data.

关键词： Mineral prospectivity modeling domain adaptation spatial factor feature dissimilarity kernel learning