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CHARACTERIZATION OF SOIL SURFACE ROUGHNESS FROM TERRESTRIAL LASER SCANNER DATA

机译:地面激光扫描仪数据的土壤表面粗糙度的表征

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The surface roughness parameters commonly used as inputs to forest radar backscatter models are the root mean square heights (RMS) s and auto-correlation length l. These parameters were traditionally estimated from a one-dimensional surface profile with limited length. The complexity of natural surfaces makes it very difficult to explicitly describe the soil roughness. Terrestrial Laser Scanner (TLS) provides a new approach for the characterization of soil surface roughness. In this paper we address the issue of soil roughness characterization from terrestrial laser scanner data. The RMS height s was calculated using TLS data and compared with field measurements. The results showed that the proposed method can be used to make soil roughness measurement so long as the data sampling frequency was high enough. The relationship between required sampling frequency and the wave length of Microwaves was derived. In addition to the soil roughness parameters, a high resolution three dimensional digital elevation model (DEM) was constructed.
机译:通常用作森林雷达反向散射模型的输入的表面粗糙度参数是根均方高度(RMS)和自动相关长度L.这些参数传统上从一维表面轮廓估计,长度有限。自然表面的复杂性使得非常难以明确描述土壤粗糙度。地面激光扫描仪(TLS)提供了一种新的土壤表面粗糙度表征的方法。在本文中,我们解决了地面激光扫描仪数据的土壤粗糙表征问题。使用TLS数据计算RMS高度S并与现场测量进行比较。结果表明,该方法可用于制造土壤粗糙度测量,只要数据采样频率足够高即可。推导了所需采样频率与微波的波长之间的关系。除了土壤粗糙度参数之外,构建了高分辨率三维数字高度模型(DEM)。

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