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首页> 外文期刊>KSCE journal of civil engineering >Tidal Creek Extraction from Airborne LiDAR Data Using Ground Filtering Techniques
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Tidal Creek Extraction from Airborne LiDAR Data Using Ground Filtering Techniques

机译:使用地面过滤技术从机载激光雷达数据提取潮汐溪

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As elongated indentations or valleys in a wetland caused by tidal currents, tidal creeks act as drainage pathways and promote tidal flat evolution. Determining their geometric information is essential for topographical research of tidal flats. The airborne light detection and ranging (LiDAR) system has been the most efficient surveying technique in tidal topography because it can directly acquire precise geo-referenced point clouds for wide areas. Existing tidal creek extraction methods using airborne LiDAR data have limitations such as excessive user intervention, lack of adaptability to various shapes and sizes of tidal creeks, and decreased precision due to conversion to the digital elevation model. This study aims to overcome these limitations and effectively extract various types of tidal creeks by utilizing ground filtering which is a technique to filter off-ground objects (such as buildings, trees, etc.) in land LiDAR surveys. To derive a suitable method for tidal creek extraction, three verified ground filtering techniques, adaptive triangulated irregular network, gLiDAR, and cloth simulation filtering (CSF), were selected and tested using LiDAR point data. We modified the application procedure and optimized their parameters to enable tidal creek extraction. Our results confirmed that CSF can extract various tidal creeks with minimal user intervention. Finally, we calculated their depths and generated a tidal creek map.
机译:作为由潮流引起的湿地的细长压痕或山谷,潮汐小溪充当排水途径,促进潮汐平进化。确定它们的几何信息对于潮汐公寓的地形研究至关重要。空中光检测和测距(LIDAR)系统是潮汐地形中最有效的测量技术,因为它可以直接获取广泛区域的精确地理参考点云。现有的潮汐溪提取方法采用空机激光雷达数据具有诸如过度的用户干预,缺乏对各种形状和潮汐小溪的尺寸的适应性,以及由于转换为数字高度模型而降低的精度。本研究旨在通过利用地面过滤来克服这些限制,并有效地提取各种类型的潮汐小溪,这是一种用于在Lind LiDar调查中过滤离地物体(如建筑物,树木等)的技术。为了获得合适的潮汐溪提取方法,选择并使用LIDAR点数据选择并测试三种验证的地面滤波技术,自适应三角形不规则网络,GLIDAR和布料模拟过滤(CSF)。我们修改了应用程序,并优化了它们的参数以启用TIDal Creek提取。我们的结果证实,CSF可以通过最小的用户干预提取各种潮汐小溪。最后,我们计算了他们的深度并产生了潮汐溪地图。

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