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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >ASSESSMENT OF BIOPHYSICAL VEGETATION PROPERTIES THROUGH SPECTRAL DECOMPOSITION TECHNIQUES
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ASSESSMENT OF BIOPHYSICAL VEGETATION PROPERTIES THROUGH SPECTRAL DECOMPOSITION TECHNIQUES

机译:通过光谱分解技术对生物植被特性的评估

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This article demonstrates the use of spectral decomposition for analyzing the spectral response of different semiarid vegetation species found throughout Mediterranean Europe. Using this technique, it is possible to decompose a spectral data set into a smaller number of significant factors that represent the key variables affecting vegetation spectral response. The results presented here show how spectral decomposition can be used to determine the intrinsic number and identity of the significant factors affecting the multispectral response. For the dataset investigated here, which comprises field spectra recorded over 1130 wavelengths, using a GER single field-of-view IRIS (SIRIS) spectroradiometer, it was found that a combination of just four factors was responsible for the majority of spectral variance. Interpretation of these factors was carried out by graphical analysis, stepwise regeneration of the original spectra, and correlation with biophysical data. Considering the identity of these factors, it was found that the second most significant factor (factor 2) was strongly related to the proportion of directly irradiated green leaves within the field-of-view of the spectroradiometer. In addition, it was found that the fourth most significant factor (factor 4) provided a good summary of the spectral response of the different samples in the region of strong chlorophyll absorption. This demonstrates the possibility of using spectral decomposition techniques, particularly in environments dominated by spectrally similar vegetation classes, to model the mixed spectral population, as mixtures of fundamental biophysical parameters rather than as mixtures of the classes themselves. [References: 46]
机译:本文演示了使用光谱分解来分析整个地中海欧洲发现的不同半干旱植被物种的光谱响应。使用此技术,可以将光谱数据集分解为较少数量的重要因子,这些重要因子表示影响植被光谱响应的关键变量。此处呈现的结果显示了如何使用光谱分解来确定影响多光谱响应的重要因素的固有数量和同一性。对于此处研究的数据集,其中包括使用GER单视场IRIS(SIRIS)分光辐射计记录的超过1130个波长的现场光谱,发现只有四个因素的组合才是造成大部分光谱变化的原因。通过图形分析,原始光谱的逐步再生以及与生物物理数据的相关性来解释这些因素。考虑到这些因素的同一性,发现第二个最重要的因素(因素2)与光谱辐射仪视野内直接照射的绿叶的比例密切相关。此外,还发现第四重要因子(因子4)很好地总结了叶绿素吸收强的区域中不同样品的光谱响应。这证明了使用光谱分解技术的可能性,特别是在光谱相似的植被类别占主导的环境中,以基本生物物理参数的混合物而不是类别本身的混合物来模拟混合光谱种群。 [参考:46]

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