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How to Effectively Prevent and Mitigate Geomagnetic Hazard?

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Journal of Earth Science 2023年第4期34卷 1304-1305页

作者： xiangyun hu Bo Han Tao Yu Institute of Geophysics&Geomatics China University of GeosciencesWuhan 430074China Institute of Geological Survey China University of GeosciencesWuhan 430074China

Compared to well-known geological hazards such as earthquakes, volcanic eruptions, landslides, and mudslides, the concept of “geomagnetic hazards” is much less familiar to people. Geomagnetic hazards are intense disturbances in the Earth’ s magnetic field caused by solar flares, which can lead to geomagnetic storms. These storms ignite large geomagnetic induction currents and disrupt the global upper atmospheric and ionospheric environment.

关键词： storm geomagnetic volcanic

A Goal-Oriented Adaptive Finite Element Method for 3D Resistivity Modeling Using Dual-Error Weighting Approach

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Journal of Earth Science 2015年第6期26卷 821-826页

作者： Yixin Ye xiangyun hu Dong Xu Fundamental Science on Radioactive Geology and Exploration Technology Laboratory East China Institute of Technology hubei Subsurface Multi-scale Imaging Lab China University of Geosciences

A goal-oriented adaptive finite element（FE） method for solving 3D direct current（DC） resistivity modeling problem is presented. The model domain is subdivided into unstructured tetrahedral elements that allow for efficient local mesh refinement and flexible description of complex models. The elements that affect the solution at each receiver location are adaptively refined according to a goal-oriented posteriori error estimator using dual-error weighting approach. The FE method with adapting mesh can easily handle such structures at almost any level of complexity. The method is demonstrated on two synthetic resistivity models with analytical solutions and available results from integral equation method, so the errors can be quantified. The applicability of the numerical method is illustrated on a resistivity model with a topographic ridge. Numerical examples show that this method is flexible and accurate for geometrically complex situations.

关键词： adaptive finite element dual-error weighting approach unstructured mesh 3D resistivity.

2D magnetotelluric inversion based on ResNet

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Artificial Intelligence in Geosciences 2023年第1期4卷 119-127页

作者： LiAn Xie Bo Han xiangyun hu Ningbo Bai Institute of Geological Survey China University of GeosciencesWuhan430074China hubei Subsurface Multi-Scale Imaging Key Laboratory School of Geophysics and GeomaticsChina University of GeosciencesWuhan430074China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan430074China

In this study,a deep learning algorithm was applied to two-dimensional magnetotelluric(MT)data *** with the traditional linear iterative inversion methods,the MT inversion method based on convolutional neural networks(CNN)does not rely on the selection of the initial model parameters and does not fall into the local *** the CNN inversion models can provide a clear electrical interface division,their inversion results may remain prone to abrupt electrical interfaces as opposed to the actual underground electrical *** solve this issue,a neural network with a residual network architecture(ResNet-50)was constructed in this *** the apparent resistivity and phase pseudo-section data as the inputs and with the resistivity parameters of the geoelectric model as the training labels,the modified ResNet-50 model was trained end-to-end for producing samples according to the corresponding production strategy of the study *** experiments,the training of the ResNet-50 with the dice loss function effectively solved the issue of over-segmentation of the electrical interface by the cross-entropy function,avoided its abrupt inversion,and overcame the computational inefficiency of the traditional iterative *** proposed algorithm was validated against MT data measured from a geothermal field prospect in huanggang,hubei Province,which showed that the deep learning method has opened up broad prospects in the field of MT data inversion.

关键词： Magnetotellurics 2D inversion Residual network Deep learning

Multiscale anisotropic diffusion for ringing artifact suppression in geophysical deconvolution data

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Earthquake Science 2016年第4期29卷 215-220页

作者： Boxin Zuo xiangyun hu Meixia Geng China University of Geosciences

Ringing artifact degradations always appear in the deconvolution of geophysical data. To address this problem, we propose a postprocessing approach to suppress ringing artifacts that uses a novel anisotropic diffusion based on a stationary wavelet transform （SWT） algorithm. In this paper, we discuss the ringing artifact suppression problem and analyze the characteristics of the deconvolu- tion ringing artifact. The deconvolution data containing ringing artifacts are decomposed into different SWT sub- bands for analysis, and a new multiscale adaptive aniso- tropic filter is developed to suppress these degradations. Finally, we demonstrate the performance of the proposed method and describe the experiments in detail.

关键词： Deconvolution Ringing artifacts Anisotropicdiffusion Stationary wavelet transform algorithm Multiscale

Mantle plume trail beneath the ca.1.1 Ga North American Midcontinent Rift revealed by magnetotelluric data

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National Science Review 2024年第8期11卷 146-156页

作者： Wule Lin Adam Schultz Bo Yang Lyal B.Harris xiangyun hu hubei Subsurface Multi-scale Imaging Key Laboratory School of Geophysics and Geomatics China University of Geosciences Department of Ocean Science and Engineering Southern University of Science and Technology Advanced Institute for Ocean Research Southern University of Science and Technology College of Earth Ocean and Atmospheric SciencesOregon State University Key Laboratory of Ocean and Marginal Sea Geology South China Sea Institute of Oceanology Chinese Academy of Sciences China-Pakistan Joint Research Center on Earth Sciences CAS-HEC Eau Terre Environnement Research Centre Institut National de la Recherche Scientifique

Whilst the 1.1 Ga North American Midcontinent Rift(MCR) system is formed in association with the Keweenaw mantle plume,the absence of a northern third rift arm or aulacogen(a general characteristic of mantle plumes) has previously not been well *** help clarify this unusual plume-rift relationship and to better establish the region affected by the Keweenaw mantle plume,we present the first electrical resistivity model of the MCR derived from 3D inversion of EarthScope USArray and Lithoprobe magneto telluric(MT) data,extending northwards into the Archean Superior *** model shows a prominent highly conductive anomaly trending NW-SE at the base of Western Superior's cratonic lithospheric mantle,cross-cutting and extending for over 300 km on both sides of the western rift *** propose that this anomaly reflects the ancient signature of a plume trail,resulting from metasomatism and/or partial melting of the sulfide-rich basal lithospheric mantle during impingement of the Keweenaw mantle plume.

关键词： magnetotelluric Midcontinent Rift Keweenaw mantle plume Superior Province North America

A regularized magnetotelluric inversion with a minimum support gradient constraint

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Earthquake Science 2020年第3期33卷 130-140页

作者： Junjun Zhou xiangyun hu Tiaojie Xiao Institute of Geophysics and Geomatics China University of GeosciencesWuhan 430000China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China

Magnetotelluric(MT)inversion is an illposed problem and the standard way to address it is through regularization,by adding a stabilizing functional to the data objective functional in order to obtain a stable *** traditional stabilizing functionals,in which a low-order differential operator is used,yield a smooth solution that may not be appropriate when anomalies occur in block *** some cases the focused imaging of a sharp electrical boundary is *** though various experiments have used stabilizing functionals that are suitable to obtain a clear and sharp boundary,such as the minimum support(MS)and the minimum gradient support(MGS)functionals,there are still some limitations in *** this paper,the minimum support gradient(MSG)is proposed as the stabilizing *** the uniform regularization framework,a regularized inversion with a variety of stabilizing functionals is performed and the inversion results are *** study shows that MSG inversion can not only obtain a clearly focused inversion but also a quite stable and robust one.

关键词： magnetotelluric focus inversion sharp boundary regulafization

Luojia-HSSR:A high spatial-spectral resolution remote sensing dataset for land-cover classification with a new 3D-HRNet

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Geo-Spatial Information Science 2023年第3期26卷 289-301页

作者： Yue Xu Jianya Gong Xin huang xiangyun hu Jiayi Li Qiang Li Min Peng School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina hubei Luojia Laboratory WuhanChina Institute of Artificial Intelligence in Geomatics Wuhan UniversityWuhanChina Data Center Shenyang Surveying and Mapping Institute Co.LtdShenyangChina

High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing *** there are already some HSSR datasets for deep learning model training and testing,the data volume of these datasets is small,resulting in low classification accuracy and weak generalization ability of the trained *** this paper,an HSSR dataset Luojia-HSSR is constructed based on aerial hyperspectral imagery of southern Shenyang City of Liaoning Province in *** our knowledge,it is the largest HSSR dataset to date,with 6438 pairs of 256×256 sized samples(including 3480 pairs in the training set,2209 pairs in the test set,and 749 pairs in the validation set),covering area of 161 km2 with spatial resolution 0.75 m,249 Visible and Near-Infrared(VNIR)spectral bands,and corresponding to 23 classes of field-validated ground *** is an ideal experimental data for spatial-spectral feature ***,a new deep learning model 3D-HRNet for interpreting HSSR images is *** conv-neck in HRNet is modified to better mine the spatial information of the ***,a 3D convolution module with attention mechanism is designed to capture the global-local fine spectral information ***,the 3D convolution is inserted into the HRNet to optimize the *** experiments show that the 3D-HRNet model has good interpreting ability for the Luojia-HSSR dataset with the Frequency Weighted Intersection over Union(FWIoU)reaching 80.54%,indicating that the Luojia-HSSR dataset constructed in this paper and the proposed 3D-HRnet model have good applicable prospects for processing HSSR remote sensing images.

关键词： High Spatial and Spectral Resolution(HSSR) remotesensing image classification deep learning Convolutional Neural Network(CNN)

LuoJiaAI:A cloud-based artificial intelligence platform for remote sensing image interpretation

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Geo-Spatial Information Science 2023年第2期26卷 218-241页

作者： Zhan Zhang Mi Zhang Jianya Gong xiangyun hu Hanjiang Xiong huan Zhou Zhipeng Cao State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina School of Remote Sensing and Information Engineering Wuhan UniversityWuhanChina Department of Land-Surveying and Geo-Informatics Hong Kong Polytechnic UniversityHong KongChina

The rapid processing,analysis,and mining of remote-sensing big data based on intelligent interpretation technology using remote-sensing cloud computing platforms(RS-CCPs)have recently become a new *** existing RS-CCPs mainly focus on developing and optimizing high-performance data storage and intelligent computing for common visual representation,which ignores remote sensing data characteristics such as large image size,large-scale change,multiple data channels,and geographic knowledge embedding,thus impairing computational efficiency and *** construct a LuoJiaAI platform composed of a standard large-scale sample database(LuoJiaSET)and a dedicated deep learning framework(LuoJiaNET)to achieve state-of-the-art performance on five typical remote sensing interpretation tasks,including scene classification,object detection,land-use classification,change detection,and multi-view 3D *** details of the LuoJiaAI application experiment can be found at the white paper for LuoJiaAI industrial *** addition,LuoJiaAI is an open-source RS-CCP that supports the latest Open Geospatial Consortium(OGC)standards for better developing and sharing Earth Artificial Intelligence(AI)algorithms and products on benchmark *** narrows the gap between the sample database and deep learning frameworks through a user-friendly data-framework collaboration mechanism,showing great potential in high-precision remote sensing mapping applications.

关键词： Artificial intelligence cloud computing platform remote-sensing intelligent interpretation sample database deep learning framework

The Deep Geophysical Structure of the Middle Section of the Longmen Mountains Tectonic Belt and its Relation to the Wenchuan Earthquake

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Acta Geologica Sinica(English Edition) 2014年第2期88卷 483-497页

作者： YU Nian WANG Xuben hu xiangyun CAI Xuelin KAN Aike ZHAO Ning Institute of Geophysics and Geomatics China University of Geosciences Institute of Geophysics Chengdu University of Technology China railway Eryuan Engineering Group Co.Ltd State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation College of Information EngineeringChengdu University of Technology

Investigation of the deep geophysical structure of the Longmen Mountains tectonic belt and its relation to the Wenchuan Earthquake is important for the study of *** using magnetotelluric sounding profiles of the Luqu-Zhongjiang and Anxian-Suining; seismic sounding profiles of the Sichuan Maowen-Chongqing Gongtan,the Qinghai huashi Gorge-Sichuan Jianyang,and the Batang-Zizhong; and magnetogravimetric data of the Longmen Mountains region,the deep geophysical structure of the Songpan-Ganzi block,the western Sichuan foreland basin,and the Longmen Mountains tectonic belt and their relation was *** eastward extrusion of the Qinghai-Tibet Plateau thrusts the Songpan-Ganzi block upon the Yangtze block,which obstructs the eastward movement of the Qinghai-Tibet *** Maoxian-Wenchuan,Beichuan-Yingxiu,and Anxian-Guanxian faults of the Longmen Mountains fault belt dip to northwest with different dip angles and gradually converge in the deeper *** structure suggests that an intracrustal low-velocity,low-resistivity,and high-conductivity layer is common between the middle and upper crust west of the Longmen Mountains tectonic belt but not in the upper Yangtze *** Sichuan Basin has a thick low-resistance sedimentary layer on a stable high-resistance basement; moreover,there are secondary paleohighs and depression structures at the lower part of the western Sichuan foreland basin with characteristic of high magnetic anomalies,whereas the Songpan-Ganzi block has a high resisitivity cover of upper crust and continues to a low-resistance *** the Longmen Mountains tectonic belt as the boundary,there are Bouguer gravity anomalies of ＂one belt between two zones.＂ Thus,we infer that there is a corresponding relation between the inferred crystalline basement of the Songpan block and the underlying basin basement of the Longmen Mountains fault ***,there may be an extensive ancient Yangtze block,which is west of the Ru

关键词： Longmen Mountains tectonic belt Wenchuan earthquake magnetotelluric sounding seismic sounding Songpan-Ganzi folded belt Qinghai-Tibet plateau