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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Sensitivity of DEM, slope, aspect and watershed attributes to LiDAR measurement uncertainty
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Sensitivity of DEM, slope, aspect and watershed attributes to LiDAR measurement uncertainty

机译:DEM,坡度,坡度和分水岭属性对LiDAR测量不确定度的敏感性

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Knowledge of LiDAR measurement uncertainty and its propagation into derived geospatial products is important for conscientious application of LiDAR products to environmental modeling, planning and decision making. This study simulates theoretical error limits of LiDAR elevations based on survey acquisition parameters and terrain conditions and applies a Monte Carlo simulation approach to determine the uncertainty in a DEM, grid based slope and aspect maps, watershed area and a stream network delineation. A cell-by-cell assessment of the DEM for hydrological network extraction is also provided through the Gyasi-Agyei et al. (1995) suitability metric. Results show that DEM uncertainty generally ranged between 0.025 and 0.060 m, slope uncertainty ranged between 0.6 and 1.5 degrees, and aspect uncertainty ranged between 2.7 and 24.1 degrees for the given case study site. DEM uncertainty and slope uncertainty were correlated with the incidence angle between the laser pulse and the terrain, described with a piecewise linear function. Uncertainty in aspect showed a correlation with terrain slope and could be described with a decreasing power function. The variation in watershed area was less than 1% of total watershed area indicating it was not sensitive to LiDAR measurement errors for the selected case study site. Stream network length variability was 1.5% of total length, but increased as the analyzed area decreased. Areas of 1 ha showed relative standard deviations of stream network length of similar to 26%. These results can be used to optimise LiDAR survey data collection configuration and in the design of tools to ensure the objectives and uncertainty requirements of projects requiring terrain derivative products are successfully achieved. (C) 2016 Elsevier Inc. All rights reserved.
机译:LiDAR测量不确定度及其在衍生的地理空间产品中的传播的知识对于将LiDAR产品认真应用于环境建模,规划和决策至关重要。这项研究基于调查采集参数和地形条件模拟了LiDAR海拔的理论误差极限,并应用了蒙特卡罗模拟方法来确定DEM,基于网格的坡度和纵横图,分水岭区域和河流网络轮廓线中的不确定性。还通过Gyasi-Agyei等人对用于水文网络提取的DEM进行了逐个单元的评估。 (1995)适用性指标。结果表明,对于给定的案例研究站点,DEM的不确定度通常在0.025至0.060 m之间,坡度不确定度在0.6至1.5度之间,而宽高比不确定度在2.7至24.1度之间。 DEM不确定性和坡度不确定性与激光脉冲和地形之间的入射角相关,用分段线性函数描述。方面的不确定性显示出与地形坡度的相关性,可以用递减的幂函数来描述。流域面积的变化小于总流域面积的1%,表明它对所选案例研究站点的LiDAR测量误差不敏感。河网长度变化为总长度的1.5%,但随着分析面积的减少而增加。 1公顷的面积显示出河网长度的相对标准偏差接近26%。这些结果可用于优化LiDAR测量数据收集配置以及工具设计,以确保成功实现需要地形衍生产品的项目的目标和不确定性要求。 (C)2016 Elsevier Inc.保留所有权利。

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