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    Delineating Beach and Dune Morphology from Massive Terrestrial Laser-Scanning Data Using <i>Generic Mapping Tools</i>

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    %28ASCE%29SU.1943-5428.0000223.pdf (6.192Mb)
    Date
    2017
    Author
    Xin Zhou
    Guoquan Wang
    Yan Bao
    Lin Xiong
    Veronica Guzman
    Timothy J. Kearns
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    Abstract
    Terrestrial laser-scanning (TLS) techniques have been proven to be efficient tools for collecting three-dimensional high-density and high-accuracy point clouds for coastal research and resource management. However, TLS collects a massive number of surveying points. The processing and presenting of the large volumes of data sets is always a challenge for research when targeting a large area with high resolution. This article introduces a practical workflow using shell-scripting techniques to chain together tools from the Generic Mapping Tools (GMT), Geographic Resources Analysis Support System (GRASS), and other command-based open-source utilities for automating TLS data processing. TLS point clouds acquired in the beach and dune area near Freeport, Texas, in May 2015 were used for the case study. GMT is an open-source collection of programs designed for manipulating and displaying geographic data sets. Shell scripts for rotating the coordinate system, removing anomalous points, assessing data quality, generating high-accuracy bare-earth digital elevation models (DEMs), and quantifying changes of beach and sand dune features (shoreline, cross-shore section, dune ridge, toe, and volume) are presented in this article. This investigation indicated that GMT provides efficient and robust programs for regridding and filtering massive TLS point-cloud data sets, generating and displaying high-resolution DEMs, and, finally, producing publication-quality maps and graphs. The methods and scripts presented in this article will benefit a large research and application community of geomorphologists, geologists, geophysicists, engineers, and others who need to handle large volumes of topographic data sets and generate high-resolution DEMs.
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    http://138.201.223.254:8080/yetl1/handle/yetl/4242460
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