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LaDiCaoz and LiDARimager—MATLAB GUIs for LiDAR data handling and lateral displacement measurement

机译:LaDiCaoz和LiDARimager-用于LiDAR数据处理和横向位移测量的MATLAB GUI

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Light detection and ranging (LiDAR), high-resolution topographic data sets enable remote identification of submeter-scale geomorphic features and have proven very valuable in geologic, paleoseismic, and geomorphologic investigations. They are also useful for studies of hydrology, timber evaluation, vegetation dynamics, coastal monitoring, hill-slope processes, or civil engineering. One application for LiDAR data is the measurement of tectonically displaced geomorphic markers to reconstruct paleoearthquake slip distributionscurrently a cornerstone in the formulation of earthquake recurrence models and the understanding of seismic fault behavior. With this publication we provide two MATLAB-based graphical user interfaces (GUIs) and corresponding tutorials: LiDARimagera tool for LiDAR data handling and visualization (e.g., data cropping, generation of map- and oblique-view plots of various digital elevation model [DEM] derivatives, storable as *.jpg or *.kmz files); and LaDiCaoza tool to determine lateral displacements of offset sublinear geomorphic features such as stream channels or alluvial fan edges. While application of LaDiCaoz is closely linked to tectonogeomorphic studies, LiDARimager may find application in a wide range of studies that utilize LiDAR data visualizations. A key feature of LaDiCaoz, not available in standard geographic information system (GIS) packages, is DEM slicing and (laterally) back slipping for visual offset reconstruction assessment, improving measurement accuracy and precision. Comparison of offset measurements, made by different individuals, showed good measurement repeatability with LaDiCaoz for morphologically simple channels. Offset estimates began to vary distinctly for morphologically more complex features, attributed to different assumptions of pre-earthquake morphology and underlining the importance of a sound understanding of pre-earthquake site morphology for meaningful offset measurements.
机译:光检测和测距(LiDAR)高分辨率地形数据集可实现亚米级地貌特征的远程识别,并且在地质,古地震和地貌学研究中被证明非常有价值。它们也可用于水文学,木材评估,植被动态,海岸监测,山坡过程或土木工程的研究。 LiDAR数据的一种应用是测量构造位移的地貌标记,以重建古地震滑动分布,目前是地震复发模型制定和理解地震断层行为的基石。在此出版物中,我们提供了两个基于MATLAB的图形用户界面(GUI)和相应的教程:用于LiDAR数据处理和可视化的LiDARimagera工具(例如,数据裁剪,各种数字高程模型[DEM]的地图视图和斜视图图的生成)衍生物,可存储为* .jpg或* .kmz文件);和LaDiCaoza工具确定偏移的亚线性地貌特征(例如河道或冲积扇缘)的横向位移。尽管LaDiCaoz的应用与地貌研究紧密相关,但LiDARimager可能会在利用LiDAR数据可视化的广泛研究中找到应用。 LaDiCaoz的一个关键功能(在标准地理信息系统(GIS)软件包中不可用)是DEM切片和(横向)向后滑动,用于视觉偏移重建评估,从而提高了测量精度和精度。不同个体进行的偏移量测量的比较显示,对于形态简单的通道,LaDiCaoz具有良好的测量重复性。由于地震前形态的不同假设,并且对于形态学上更复杂的特征,偏移量估计值开始发生明显变化,这突显了对有意义的偏移量测量正确理解地震前位点形态的重要性。

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