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The impact of varied nominal posting density LIDAR data on DEM accuracy, hydraulic modeling and flood zone delineation.

机译:各种名义上发布密度的LIDAR数据对DEM精度,水力模型和洪水区轮廓的影响。

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摘要

LIDAR data has become a primary source of digital terrain information for use in hydraulic modeling and flood mapping. However, the accuracy of digital elevation models (DEMs) derived from such data has not been widely documented under various conditions. Therefore the factors that influence this accuracy are only generally understood. Based on established relationships between sampling intensity and error, nominal posting density, or the average distance between collected points, likely contributes significantly to the error budget as areas between each ground post must be interpolated. Nominal posting density is also a major cost determining factor of LIDAR data collection. Often more flight time is required as higher posting densities usually require some combination of the following: (a) lower altitude, (b) additional flight lines, or (c) a higher pulse rate. In addition to data collection requirements, the additional data volume incurred through a higher posting density requires extra storage capacity, as well as substantially greater computer and manual processing time. This research presents a methodology for establishing a relationship between nominal posting density and its effects on hydraulic modeling for flood zone delineation. LIDAR data collected at a high posting density (∼1 to 2 m) over a study area in North Carolina piedmont was systematically decimated to simulate datasets with sequentially lower posting densities. Using extensive first-order ground survey information the relative accuracy of each DEM derived from these LIDAR datasets was assessed and reported. A series of hydraulic analyses was performed utilizing standard engineering practices and modeling software (HEC-RAS). All input variables were held constant in each model run except the topographic information from the decimated LIDAR datasets. The results were compared to a hydraulic analysis performed on the un-decimated reference dataset. The sensitivity of the primary model outputs (i.e., base flood elevation and flood zone boundary) to the variation in nominal posting density is reported. The results indicate that although general error patterns are apparent visually they are not statistically significant over the posting densities tested. The flood zone extent is found to be sensitive to variations in posting density.
机译:LIDAR数据已经成为用于水力建模和洪水制图的数字地形信息的主要来源。但是,在各种情况下,从此类数据得出的数字高程模型(DEM)的准确性尚未得到广泛记录。因此,影响该精度的因素只是一般性的理解。基于采样强度与误差,标称发布密度或收集的点之间的平均距离之间的已建立关系,由于必须对每个地面站之间的区域进行插值,因此很可能对误差预算有重大贡献。标称发布密度也是LIDAR数据收集的主要成本决定因素。通常需要更长的飞行时间,因为更高的发信密度通常需要以下各项的组合:(a)较低的高度,(b)附加的飞行路线,或(c)较高的脉冲率。除了数据收集要求之外,由于较高的发布密度而导致的额外数据量还需要额外的存储容量,以及显着更长的计算机和手动处理时间。这项研究提出了一种方法,用于建立标称过帐密度与其对洪水区划定水力模型的影响之间的关系。系统地抽取了北卡罗莱纳州皮德蒙特一个研究区域内以高发布密度(约1至2 m)收集的LIDAR数据,以模拟发布密度依次降低的数据集。使用广泛的一阶地面调查信息,评估和报告了从这些LIDAR数据集得出的每个DEM的相对精度。利用标准工程实践和建模软件(HEC-RAS)进行了一系列水力分析。除了来自抽取的LIDAR数据集的地形信息之外,每个模型运行中的所有输入变量均保持恒定。将结果与对未抽取参考数据集执行的水力分析进行比较。报告了主要模型输出(即基础洪水标高和洪水区边界)对标称发布密度变化的敏感性。结果表明,尽管一般错误模式在视觉上很明显,但在测试的过帐密度上在统计上并不显着。发现洪泛区范围对发布密度的变化敏感。

著录项

  • 作者

    Raber, George Thomas.;

  • 作者单位

    University of South Carolina.;

  • 授予单位 University of South Carolina.;
  • 学科 Geography.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 78 p.
  • 总页数 78
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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