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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Development of In Situ Experiments for Evaluation of Anisotropic Reflectance Effect on Spectral Mixture Analysis for Vegetation Cover
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Development of In Situ Experiments for Evaluation of Anisotropic Reflectance Effect on Spectral Mixture Analysis for Vegetation Cover

机译：植被覆盖光谱混合分析中各向异性反射效应评估的原位实验开发

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摘要

Owing to its flexibility, spectral mixture analysis (SMA) based on the linear spectral mixing model (LSMM) is a useful tool for subpixel vegetation cover estimation. Multiple scattering and endmember spectral variability are the two reasons that produce errors in the LSMM-retrieved cover fraction estimates. Although the anisotropic reflectance properties are well documented, their effect has barely been investigated in the studies of subpixel vegetation cover estimation. This letter developed a series of controlled experiments (using a checkerboard mixture design) to evaluate the anisotropic reflectance effect (ARE) on fractional vegetation cover estimation using SMA based on the LSMM. The results illustrate that ARE has a large impact on SMA for vegetation cover estimation, and the developed approach allowing for ARE produces more accurate estimates, as the value of root-mean-square error drops more than 50%. This letter may open a new perspective for using SMA to estimate vegetation cover by emphasizing the importance of integrating ARE and characterizing anisotropic reflectance properties of an endmember class as another source of intraclass variability that is likely to be ignored.
机译：由于其灵活性，基于线性光谱混合模型（LSMM）的光谱混合分析（SMA）是用于亚像素植被覆盖率估算的有用工具。多重散射和端成员光谱变异性是在LSMM检索的覆盖率估算中产生误差的两个原因。尽管各向异性反射特性已得到充分证明，但在亚像素植被覆盖率估算研究中几乎没有研究过它们的影响。这封信开发了一系列受控实验（使用棋盘混合设计），以基于LSMM的SMA评估各向异性反射率效应（ARE）对植被覆盖率估算的影响。结果表明，ARE对SMA的植被覆盖率估计有很大影响，并且当ARE的均方根误差值下降超过50％时，允许ARE的已开发方法可以产生更准确的估计值。这封信可能会通过强调整合ARE的重要性以及将端构件类别的各向异性反射特性表征为类内变异性的另一个来源而可能打开，从而为使用SMA估算植被覆盖度开辟新的前景。

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