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Modeling hemispherical reflectance for natural surfaces based on terrestrial laser scanning backscattered intensity data

机译:基于地面激光扫描反向散射强度数据的自然表面半球反射率建模

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摘要

Independent of instrumental properties and scanning geometry, target reflectance is significantly important for terrestrial laser scanning (TLS) data processing and utilization, especially in multi-temporal and multi-sensor cases. In addition to the 3D topographic coordinates, TLS systems also record the backscattered intensity value of each point that provides additional information on the reflectance characteristics of the scanned surface. However, a number of confounding variables, particularly the distance and incidence angle, distort the ability of the original intensity to directly retrieve the target reflectance. This study proposes a new method to model the hemispherical reflectance of natural surfaces from the TLS intensity data by eliminating the effects of incidence angle and distance. The incidence angle effect is corrected by the Oren-Nayar reflectance model which takes individual surface roughness into account whereas the irregular distance effect is eliminated by reference targets without estimating the specific distance-intensity function. The Faro Focus(3D) 120 terrestrial scanner is utilized in the case study. Six typical natural surfaces are chosen as the experimental objects. Results imply that the proposed method exhibits high accuracy in retrieving reflectance values. The deviation of the retrieved reflectance values from that measured by a spectrometer is approximately 4.29% and the root mean square error (RMSE) is approximately 0.0562.
机译:与仪器特性和扫描几何形状无关,目标反射率对于地面激光扫描(TLS)数据处理和利用非常重要,特别是在多时间和多传感器情况下。除3D地形坐标外,TLS系统还记录每个点的反向散射强度值,该值提供有关扫描表面反射特性的附加信息。但是,许多混淆变量,尤其是距离和入射角,使原始强度直接获取目标反射率的能力失真。这项研究提出了一种新方法,可以通过消除入射角和距离的影响,根据TLS强度数据对自然表面的半球反射率建模。通过考虑单个表面粗糙度的Oren-Nayar反射率模型可以校正入射角效应,而参考目标可以消除不规则的距离效应,而无需估计特定的距离-强度函数。案例研究中使用了Faro Focus(3D)120地面扫描仪。选择六个典型的自然表面作为实验对象。结果表明,所提出的方法在反射率值的检索中具有很高的准确性。检索到的反射率值与由分光计测得的反射率值的偏差约为4.29%,均方根误差(RMSE)约为0.0562。

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  • 作者

    Tan, K; Cheng, XJ; Cheng, XL;

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  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 en
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