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Applied Geophysics 2024年第3期21卷 549-563,619页

作者： Bin Li qiang xu qiang Cheng Tian-Xiang Liu Jian-hua Yu Yu-jie {3. Feng Wang Sichuan Highway Planning SurveyDesign and Research Institute Ltd.SichuanChengdu 610041China chengdu university of technology State Key Laboratory of Geohazard Prevention and Geoenvironment ProtectionSichuanChengdu 610059China

A wide range of terrain features and landforms,which are exemplified by intricate geological formations and diverse rock compositions,are found in the western mountainous regions of *** areas frequently encounter geological *** one of the natural disasters,landslides lead to considerable loss of human life and *** mitigation of the losses caused by landslide disasters,a necessary measure for disaster prevention and mitigation involves conducting detailed investigations and monitoring of landslides,which is also the cornerstone of landslide *** study compares and analyzes the feasibility of the magnetotelluric detection method for landslides using the results of engineering geological surveys and landslide *** study aims to address the scientific problem of the validity of using magnetotelluric methods to detect landslide development *** Tangjiawan landslide signal on the left side of the K94+000~K94+145 section of the Wenma Expressway is analyzed by employing engineering geological survey,magnetotelluric detection,landslide monitoring,landslide analysis,and other *** results provide the static electrical characteristics of lithology,structure,and groundwater,as well as the dynamic electrical characteristics of landslide *** study focuses on analyzing the relationship between the methods of magnetotelluric detection and engineering geological surveys and the results of landslide *** workflow and methods for data collection,processing,inversion,interpretation,and analysis using the magnetotelluric method to detect the dynamic development process of landslides are presented in the *** conclusions indicate a strong correlation between the dynamic changes in magnetotelluric wave impedance with the surface displacement of landslides and the dynamic changes in *** use of the magnetotelluric method for landslide detection and monitoring is a fe

关键词： Landslide Magnetotelluric method Geophysics Engineering Geology Landslide Monitoring

A Simple Lumped Mass Model to Describe Velocity of Granular Flows in a Large Flume

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Journal of Mountain Science 2012年第2期9卷 221-231页

作者： YANG Qingqing CAI Fei UGAI Keizo su Zhiman HUANG Runqiu xu qiang Department of Civil and Environmental Engineering Gunma University Kiryu 3768515 Japan Institute of Mountain Hazards and Environment Chinese Academy of Sciences Chengdu 610041 China state key laboratory of Geo-Hazard Prevention and Geo-Environment {3. Chengdu University of Technology Chengdu 610059 China

This paper presents a lumped mass model to describe the run-out and velocity of a series of large flume tests,which was carried out to investigate some propagation mechanisms involved in rapid,dry,dense granular flows and energy transformation when the flows encountered obstacles and reoriented their movement *** between predicted and measured results show that the trend of predicted velocities was basically matched with that of measured *** scrutiny of test videos reveals that subsequent particles with a higher velocity collided with slowed fronts to make them accelerate. However,this simple model cannot reflect collisions between particles because it treated released materials as a rigid ***,the predicted velocity was somewhat lower than the measured velocity in most *** the flow changed its direction due to the variation in slope inclination,the model predicted a decrease in *** predicted decrease in velocity was less than the measured one within a reasonable range of 10% or *** some cases in which a convexity was introduced,the model also predicted the same trend of velocities as measured in the *** velocity increased greatly after the materials took a ballistic trajectory from the vertex of the convexity,and reduced dramatically when they finally made contact with the base of the lower *** difference between prediced and measured decrease in velocity was estimated to be about 5% due to the ***,the simple lumped mass model based on the energy approach could roughly predict the run-out and velocity of granular flows,although it neglected internal deformation,intergranular collision and friction.

关键词： Granular flow Large-scale flume test Mass-front velocity Deposit characteristic

Application of deep learning in ecological resource research:Theories, methods, and challenges

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Science China Earth Sciences 2020年第10期63卷 1457-1474页

作者： Qinghua GUO Shichao JIN Min LI Qiuli YANG Kexin xu Yuanzhen JU Jing ZHANG Jing xuAN Jin LIU Yanjun su {3. xu Yu LIU state key laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing 100093China university of Chinese Academy of Sciences Beijing 100049China state key laboratory of Systematic and Evolutionary Botany Institute of BotanyChinese Academy of SciencesBeijing 100093China state key laboratory of Geohazard Prevention and {3. protection Chengdu University of TechnologyChengdu 610059China Institute of Remote Sensing and Geographical Information Systems Peking UniversityBeijing 100871China

Ecological resources are an important material foundation for the survival,development,and self-realization of human ***-depth and comprehensive research and understanding of ecological resources are beneficial for the sustainable development of human *** in observation technology have improved the ability to acquire long-term,cross-scale,massive,heterogeneous,and multi-source *** resource research is entering a new era driven by big *** statistical learning and machine learning algorithms have problems with saturation in dealing with big *** learning is a method for automatically extracting complex high-dimensional nonlinear features,which is increasingly used for scientific and industrial data processing because of its ability to avoid saturation with big *** promote the application of deep learning in the field of ecological resource research,here,we first introduce the relationship between deep learning theory and research on ecological resources,common tools,and ***,applications of deep learning in classification and recognition,detection and localization,semantic segmentation,instance segmentation,and graph neural network in typical spatial discrete data are presented through three cases:species classification,crop breeding,and vegetation ***,challenges and opportunities for the application of deep learning in ecological resource research in the era of big data are summarized by considering the characteristics of ecological resource data and the development status of deep *** is anticipated that the cooperation and training of cross-disciplinary talents may promote the standardization and sharing of ecological resource data,improve the universality and interpretability of algorithms,and enrich applications with the development of hardware.

关键词： Ecological resources Deep learning Neural network Big data Theory and tools Application and challenge

基于动态数据驱动的地质灾害监测预警系统设计与实现

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成都理工大学学报（自然科学版） 2018年第5期45卷 615-625页

作者：苏白燕许强黄健梁繁地质灾害防治与地质环境保护国家重点实验室(成都理工大学) 成都610059 四川省国土资源资料馆成都610045

基于地质灾害诱发因素与形成机理,针对地质灾害传统数据管理、实时监测数据处理与分析、预警模型库建设等问题,结合动态数据驱动、多源数据可视化及监测数据实时传输等技术,建立基于动态数据驱动技术的地质灾害监测自动预警方法体系,并... 详细信息

基于地质灾害诱发因素与形成机理,针对地质灾害传统数据管理、实时监测数据处理与分析、预警模型库建设等问题,结合动态数据驱动、多源数据可视化及监测数据实时传输等技术,建立基于动态数据驱动技术的地质灾害监测自动预警方法体系,并采用阈值判别预警、过程跟踪预警以及时空信息的综合分析预警方法,充分采用服务流引擎技术与数据库技术,研制基于网络环境的新型地质灾害动态监测系统,以实现灾害信息实时查询、处理与分析、动态监测曲线的绘制及灾害自动预警等功能。以甘肃省黑方台黄土滑坡监测示范区为例,验证构建的地质灾害实时监测数据与预警模型服务流,系统能够实时反映灾害体的变形情况,并成功预警了黑方台陈家6#滑坡。

关键词：地质灾害监测预警数据驱动技术服务流引擎技术预警模型

使用宽频带地震记录研究2017年6月24日茂县新磨滑坡的动力学过程

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地球物理学报 2018年第10期61卷 4055-4062页

作者：黄兴辉李正媛余丹许强苏金蓉中国地震台网中心北京100045 地质灾害防治与地质环境保护国家重点实验室成都理工大学成都610059 四川省地震局成都610041

北京时间2017年6月24日5时3.分左右,四川省茂县叠溪镇新磨村发生大型岩质滑坡.体积约4.3.106 m3.巨型岩体从山顶脱落,顺坡滑行约2.6km后破碎沉积;碎屑物掩埋了整个新磨村,造成了巨大的人员伤亡和财产损失.本文使用来自滑坡周围的10个... 详细信息

北京时间2017年6月24日5时3.分左右,四川省茂县叠溪镇新磨村发生大型岩质滑坡.体积约4.3.106 m3.巨型岩体从山顶脱落,顺坡滑行约2.6km后破碎沉积;碎屑物掩埋了整个新磨村,造成了巨大的人员伤亡和财产损失.本文使用来自滑坡周围的10个地震台站的宽频带观测资料的长周期信号反演了这次滑坡的受力时间函数;同时使用逐步细化的格点搜索方法得到了滑坡的位置,与其真实位置一致;根据反演的受力时间函数计算了滑坡过程中滑体的运动学参数,得到的滑体运动轨迹与实际路径吻合.综合分析地震信号、受力时间函数和运动学参数表明,本次滑坡主运动的持续时间约为79s;脱落岩体在5∶3.∶50.2启动后持续加速,在5∶3.∶3..2达到速度峰值,约为52.1m·s-1;这段时间内岩体没有明显的破碎;之后,岩体开始铲刮并裹挟古滑坡造成的碎屑沉积物,自身也开始破碎解体,总体开始减速运动,直到5∶40∶9.2主运动停止;此后,小规模的碎屑散落又持续了约10s的时间.

关键词：新磨滑坡宽频带地震信号受力时间函数动力学过程

机器学习在滑坡智能防灾减灾中的应用与发展趋势

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地球科学 2023年第5期48卷 1657-1674页

作者：窦杰向子林许强郑鹏麟王协康苏爱军刘军旗罗万祺中国地质大学湖北巴东地质灾害国家野外科学观测研究站湖北武汉430074 成都理工大学地质灾害防治与地质环境保护国家重点实验室四川成都610059 四川大学水力学与山区河流开发保护国家重点实验室四川成都610065

滑坡灾害易发频发、点多面广、隐蔽性强、危害严重.开展“天‒空‒地‒深”观测一体化的滑坡早期识别、易发性评价及预测预报,对于保障人民生命和财产安全,推进滑坡灾害防治能力现代化具有重要意义.目前,依靠人工解译的滑坡识别耗时耗力,... 详细信息

滑坡灾害易发频发、点多面广、隐蔽性强、危害严重.开展“天‒空‒地‒深”观测一体化的滑坡早期识别、易发性评价及预测预报,对于保障人民生命和财产安全,推进滑坡灾害防治能力现代化具有重要意义.目前,依靠人工解译的滑坡识别耗时耗力,采用启发式模型的滑坡易发性评价不能较好地探明环境因子之间的非线性关系,基于传统监测数据的滑坡预测预报精度较低.机器学习算法凭借其强大的非线性处理能力及鲁棒性等优势,逐渐广泛应用于滑坡智能防灾减灾中.基于此,本研究系统阐述了机器学习在滑坡灾害早期识别、易发性评价及预测预报等方面的具体应用,综述了多种机器学习算法在上述3.领域中运用的优劣,最终对机器学习在滑坡灾害中未来的发展趋势进行了展望.

关键词：滑坡灾害可解释性机器学习滑坡演化知识-数据-机理三驱动智能防灾减灾激光雷达工程地质.