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ON THE CLASSIFICATION OF TREE SYSTEMS USING SPECTRAL MULTI-ANGULAR INFORMATION

机译:谱多角度信息的树系统分类研究

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Multi-angular spectral information has been used to increase precision in classifying crops and natural vegetation. These classification systems now use only spectral information with a scheme of multivariate analysis or of decision trees, among others. In this paper, the characterization schemes of multiangular spectral information associated with vegetation and its use in classification systems are discussed. To review the feasibility of using multi-angular spectral data, a maquette-type experiment was designed for tree systems with five forest species. Measurements taken were associated with the bidirectional reflectance distribution function (BRDF). The multi-angular information was modeled in a compact form and used to define a general parameter, the slope, which comprises all the angular variation of the reflectances. The results show that, with the vegetation background remaining fixed, it is possible to discriminate tree systems, and when the vegetation background varies and there is little canopy cover, confusion arises but decreases in the measure that canopy cover increases.
机译:多角度光谱信息已用于提高对农作物和自然植被进行分类的精度。这些分类系统现在仅使用光谱信息以及多元分析方案或决策树方案。本文讨论了与植被相关的多角度光谱信息的表征方案及其在分类系统中的应用。为了回顾使用多角度光谱数据的可行性,设计了一种马盖特型实验,用于具有五种森林树种的树木系统。进行的测量与双向反射率分布函数(BRDF)相关。多角度信息以紧凑的形式建模,并用于定义一个通用参数,即斜率,该斜率包括反射率的所有角度变化。结果表明,在植被背景保持不变的情况下,可以区分树木系统,并且当植被背景变化且树冠覆盖较少时,会出现混乱,但减少了树冠覆盖的程度。

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