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A methodology for processing raw LiDAR data to support urban flood modelling framework

机译：一种处理原始LiDAR数据以支持城市洪水建模框架的方法

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摘要

An assessment has been carried out to study the performance of seven different LiDAR filtering algorithms and to evaluate their suitability for urban flood modelling applications. It was found that none of these algorithms can be regarded as fully suitable to support such work in its present form. The paper presents the augmentation of an existing Progressive Morphological filtering algorithm for processing raw LiDAR data to support a 1D/2D urban flood modelling framework. The existing progressive morphological filtering algorithm was modified to incorporate buildings with basement, passage buildings and solid buildings and its value was demonstrated on a case study from Kuala Lumpur, Malaysia. The model results were analysed and compared against recorded data in terms of flood depths, flood extents and flood velocities. The difference in flood depths of approximately 40% was observed between a model that uses a DTM modified by the progressive morphological filtering algorithm and the predictions of other models. The overall results suggest that incorporation of building basements within the DTM can lead to a significant difference in the model results with a tendency towards overestimation for those models which do not incorporate such a feature.
机译：已经进行了一项评估，以研究七种不同的LiDAR滤波算法的性能，并评估其在城市洪水建模应用中的适用性。已经发现，这些算法都不能被认为完全适合以其当前形式支持这种工作。本文提出了用于处理原始LiDAR数据以支持1D / 2D城市洪水建模框架的现有渐进式形态滤波算法的增强。对现有的渐进式形态滤波算法进行了修改，以合并具有地下室的建筑物，通道建筑物和实体建筑物，并在马来西亚吉隆坡的案例研究中证明了其价值。对模型结果进行了分析，并与记录的数据进行了比较，包括洪水深度，洪水范围和洪水速度。在使用通过逐步形态滤波算法修改的DTM的模型与其他模型的预测之间，观察到洪水深度的差异约为40％。总体结果表明，在DTM中并入建筑物地下室可能导致模型结果出现显着差异，而对于那些未包含这种功能的模型，则倾向于过高估计。

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  • 来源
    《Journal of Hydroinformatics》 |2012年第1期|p.75-92|共18页
  • 作者

    A. F. Abdullah; Z. Vojinovic; R. K. Price; N. A. A. Aziz;

  • 作者单位

    Department of Hydroinformatics and Knowledge Management, UNESCO-IHE, westvest 72611 ax Delft, Netherlands;

    Department of Hydroinformatics and Knowledge Management, UNESCO-IHE, westvest 72611 ax Delft, Netherlands;

    Department of Hydroinformatics and Knowledge Management, UNESCO-IHE, westvest 72611 ax Delft, Netherlands;

    No 22 and 24, Jalan Wangsa Delima 6, KLSC, Seksyen 5, Pusat Bandar wangsa Maju, 53300 Kuala Lumpur, Malaysia;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    digital terrain models; LiDAR filtering algorithms; urban features; urban flood modelling;

    机译：数字地形模型;LiDAR过滤算法;城市特色;城市洪水模拟;

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