Recent Advances in Geotechnical Post-earthquake Reconnaissance
Recent Advances in Geotechnical Post-earthquake Reconnaissance
复制标题
DOI：
10.3389/fbuil.2019.00005
复制
发表时间：
2019-01-28
影响因子：
3
通讯作者：
Garcia, Fernando E.
中科院分区：
文献类型：
--
作者：
Bray, Jonathan D.;Frost, James D.;Garcia, Fernando E.
现场观测在岩土工程中尤为重要，因为很难在实验室中复制数千年来自然形成的土壤沉积物的反应。详细绘制受损和未受损区域的地图为有据可查的案例历史提供了数据，这些案例历史推动了许多现行设计程序的发展。因此，记录地震的关键见解推进了研究和实践。这一直是国家科学基金会赞助的地质极端事件侦察（GEER）协会自成立以来的主要目标。GEER团队不断采用新技术来捕捉地面变形及其影响。这些技术包括光成像检测和测距（LIDAR）和运动恢复结构（SfM）图像处理技术，用于生成和可视化三维点云数据集。无人机（UAV）等新的传感器部署平台在数据收集过程中发挥着不可或缺的作用。重大事件的意外观察往往会催化新的研究方向。概述了这些最近的集成技术部署和它们在地震灾害分析的核心作用。如果能够有效地捕捉和分享其影响，就有可能通过事后研究取得重大进展。
Field observations are particularly important in geotechnical engineering, because it is difficult to replicate in the laboratory the response of soil deposits built by nature over thousands of years. Detailed mapping of damaged and undamaged areas provides the data for the well-documented case histories that drive the development of many current design procedures. Thus, documenting key insights from earthquakes advance research and practice. This has been a primary goal of the National Science Foundation-sponsored Geotechnical Extreme Events Reconnaissance (GEER) Association since its inception almost 20 years ago. New technologies are continually employed by GEER teams to capture ground deformation and its effects. These technologies include Light Imaging Detection and Ranging (LIDAR) and Structure-from-Motion (SfM) image processing techniques for generating and visualizing three-dimensional point cloud data sets. New sensor deployment platforms such as Unmanned Aerial Vehicles (UAVs) are playing an integral role in the data collection process. Unanticipated observations from major events often catalyze new research directions. An overview of some of these recent integrated technology deployments and their role at the core of earthquake disaster analysis is presented. Important advancements are possible through post-event research if their effects are captured and shared effectively.