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The effects of data reduction on LiDAR-based Digital Elevation Models

机译:数据缩减对基于LiDAR的数字高程模型的影响

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LiDAR data enables highly accurate terrain representations, however, various applications are hampered by data handling efficiency; specifically lengthy processing times. To address this, both point density reductions and the use of various resolution grids are compared as data reduction methods to test their effects on the accuracy and handling efficiency of the derived Digital Elevation Model (DEM). A series of point densities of 1%, 10%, 25%, 50% and 75% were interpolated along a range of horizontal resolutions (1-, 2-, 3-, 4-, 5-, 10-, and 30- m). Results indicate that resolution reduction provides the most efficient DEMs in terms of their data handling. DEMs generated at a 3 m resolution using all of the data points deviated less than 6% from the 1mDEM100%, while significantly only taking 10% of the processing time. Resolution reduction provided sufficient accuracies for varying terrain complexities.
机译:LiDAR数据可实现高精度的地形表示,但是,各种应用受到数据处理效率的限制;特别是漫长的处理时间。为了解决这个问题,将点密度降低和使用各种分辨率网格作为数据缩减方法进行了比较,以测试它们对导出的数字高程模型(DEM)的准确性和处理效率的影响。沿一系列水平分辨率(1-,2-,3-,4-,5-,10-和30- m)。结果表明,分辨率降低在数据处理方面提供了最有效的DEM。使用所有数据点以3 m分辨率生成的DEM与 1m DEM100%的偏差小于6%,而仅花费了10%的处理时间。分辨率降低为各种复杂地形提供了足够的精度。

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