Development of In Situ Experiments for Evaluation of Anisotropic Reflectance Effect on Spectral Mixture Analysis for Vegetation Cover
Development of In Situ Experiments for Evaluation of Anisotropic Reflectance Effect on Spectral Mixture Analysis for Vegetation Cover
复制标题
评价各向异性反射率对植被覆盖光谱混合分析影响的原位实验的发展
DOI：
10.1109/lgrs.2016.2531743
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发表时间：
2016
影响因子：
4.8
通讯作者：
Long Di
中科院分区：
文献类型：
--
作者：
Tong Xin;Liu Tingxi;Singh Vijay P.;Duan Limin;Long Di
基于线性光谱混合模型(LSMM)的光谱混合分析(SMA)由于其灵活性，是一种有用的亚像元植被覆盖估算工具。多重散射和端元光谱变异性是导致LSMM反演覆盖率估计误差的两个原因。尽管各向异性反射率特性已有很好的文献记载，但其在亚像元植被覆盖估计研究中的影响却鲜有报道。本文开展了一系列现场对照试验(采用棋盘混合设计)，以评价各向异性反射比(ARE)对基于LSMM的SMA植被覆盖度估测的影响。结果表明，ARE对SMA的植被覆盖估计影响较大，当均方根误差下降50%以上时，考虑ARE的方法可以得到更准确的估计结果。这封信可能会为使用SMA估计植被覆盖度打开一个新的视角，强调积分ARE的重要性，并将端员类的各向异性反射特性描述为另一个可能被忽略的类内可变性的来源。
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 in situ 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.