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AN INTEGRATED APPROACH TO ACCURATE DEM GENERARTION USING AIRBORNE FULL WAVEFORM LIDAR DATA

机译:使用空机全波形LIDAR数据准确DEM生成的综合方法

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In this study, full waveform LiDAR data were exploited to improve the generation of a large-scale digital elevation model (DEM). Building on the methods of progressive generation of triangulation irregular network (TIN) model reported in the literature, we proposed an integrated approach. In this method, echo detection, terrain identification, and TIN generation were performed synergically and iteratively, instead of their separate determinations as in most DEM generation methods. This method started with a TIN model made up of terrain points detected using a morphological opening operation and a curve matching method. For any given TIN facet, the full waveforms of the return associated with the laser pulses interacting with this TIN facet were examined near the surface for any terrain echoes. The TIN was then updated using the newly detected terrain points. These processes were iterated until no new terrain points were identified. The developed method was tested on a data set collected by a Riegl LMS Q-560 scanner over a study area near Sault Ste. Marie, Ontario, Canada (46 deg 33 min 56 sec N, 83 deg 25 min 18 sec W). The results demonstrated that 30percent more terrain points were identified under shrubs and trees using this integrated approach, compared with the commonly used Gaussian decomposition method. The DEMs generated by the developed method exhibited more details in the terrain for two test sites than those obtained by using the TerraS can software.
机译:在本研究中,利用全波形激光雷达数据来改善大规模数字高度模型(DEM)的产生。建立在文献中报告的三角化不规则网络(TIN)模型的渐进发电方法,我们提出了一种综合方法。在该方法中,协同和迭代地进行回声检测,地形识别和锡产生,而不是它们在大多数DEM生成方法中的单独确定。该方法以使用形态开放操作和曲线匹配方法检测到的地形点组成的TIN模型。对于任何给定的锡壳,在表面附近检查与与该锡壳相互作用的激光脉冲相关联的返回的完整波形。然后使用新检测到的地形点更新锡。迭代这些过程,直到没有确定新的地形点。在Sault STE附近的研究区域,在RIEGL LMS Q-560扫描仪收集的数据集上测试了开发的方法。加拿大安大略省玛丽(46米56秒,83°25 min 18秒)。结果表明,与常用的高斯分解方法相比,使用这种综合方法在灌木和树木下鉴定了30个地形点。由开发方法产生的DEM在地形中展示了比使用Terras软件所获得的地形的更多细节。

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