Exploring the Influence of Various Factors on Slope Estimation Using Large-Footprint LiDAR Data
Exploring the Influence of Various Factors on Slope Estimation Using Large-Footprint LiDAR Data
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DOI：
10.1109/tgrs.2018.2840725
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发表时间：
2018-06
影响因子：
8.2
通讯作者：
S. Nie;Cheng Wang;X. Xi;Guoyuan Li;Shezhou Luo;Xuebo Yang;Pu Wang;Xiaoxiao Zhu
中科院分区：
文献类型：
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作者：
S. Nie;Cheng Wang;X. Xi;Guoyuan Li;Shezhou Luo;Xuebo Yang;Pu Wang;Xiaoxiao Zhu
足迹内坡度的准确估计对于利用卫星光探测和测距（LiDAR）数据测量地表特征具有重要意义。以前已经提出了几种模型的斜率估计，但是，这些模型在准确性或适用性方面都有局限性。因此，本文的主要目的是探讨各种因素的影响（例如，地面垂直范围、足迹大小、足迹形状和足迹方向）对坡度估计的影响，以便使用大足迹波形LiDAR数据更好地估计足迹内坡度。结果表明，地面垂直度与足迹尺度耦合效应引起的绝对坡度误差随地面垂直度与足迹尺度之比的增大而增大，而相对坡度误差则随地面垂直度与足迹尺度之比的增大而增大。当足迹偏心率较小时，由足迹形状引起的斜率误差相对较小。然而，由于足迹形状的斜率误差迅速增长时，足迹偏心率变得更大，因此，它是必要的，以充分考虑足迹形状的影响，在足迹内斜率估计。此外，结果表明，坡度误差的变化规律的基础上的足迹方向和地形的角度之间的交叉角。本文还提供了一个简单和实用的模型内的足迹坡度估计的确定指导。最佳模型的确定取决于相交角的大小。一旦给定交集值，就可以很容易地确定最佳模型。使用最佳模型，可以高精度地估计足迹内地形坡度。
The accurate estimation of within-footprint slope is very important for measuring earth’s surface characteristics using satellite light detection and ranging (LiDAR) data. Several models have previously been proposed for slope estimation; however, these models have limitations in either accuracy or applicability. Therefore, the main purpose of this paper is to explore the influence of various factors (e.g., ground vertical extent, footprint size, footprint shape, and footprint orientation) on slope estimation to better estimate the within-footprint slope using large-footprint waveform LiDAR data. The results indicated that the absolute slope error due to the coupling effect of ground vertical extent and footprint size increased with an increase in the ratio of ground vertical extent and footprint size, while the relative slope error had an opposite trend. The slope error caused by footprint shape was relatively low when the footprint eccentricity was small. However, the slope error due to footprint shape grew rapidly when the footprint eccentricity became larger; thus, it is essential to fully take into account the influence of footprint shape on within-footprint slope estimation. In addition, the results suggest that the slope error changed regularly based on the intersection angle between footprint orientation and terrain aspect. This paper also provided guidance for the determination of an easy and practical model for within-footprint slope estimation. The determination of best model is dependent on the value of intersection angle. Once the intersection value is given, the best model can easily be determined. Using the best model, the within-footprint terrain slope can be estimated with high accuracy.