Light detection and ranging (LiDAR), highresolution topographic data sets enable remote identifi cation of submeter-scale geomorphic features and have proven very valua ble 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 measure ment of tectonically displaced geomorphic markers to reconstruct paleoearthquake slip distributions-currently a cornerstone in the formulation of earthquake recurrence models and the understanding of seismic fault be havior. With this publication we provide two MATLAB-based graphical user interfaces (GUIs) and corresponding tutorials: LiDARimager-a 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 fi les); and LaDiCaoz-a 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 fi nd 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 measure ment 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.
ASJC Scopus subject areas