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由于地表覆盖的复杂性,在遥感影像中存在混合像元现象。文中对混合像元分解模型进行梳理,并针对线性混合像元分解在林业中的应用做了分类总结。目前混合像元分解模型主要有线性、概率、几何光学、随机几何与模糊模型5种,不同模型所需参数与输出结果也存在一定差异。其中线性混合模型在林业中的应用最为广泛,主要有土地利用分类与变化监测、森林灾害监测、稀疏植被探测、城市植被丰度估算、不均匀冠层参数估算等方面。
Because of the complexity of surface coverage, there are mixed pixel phenomena in remote sensing images. In this paper, the mixed pixel decomposition model is combed, and the application of linear mixed pixel decomposition in forestry is classified. At present, there are five kinds of mixed pixel decomposition models: linearity, probability, geometric optics, stochastic geometry and fuzzy model. There are also some differences between the parameters and output results of different models. Among them, the linear mixed model is the most widely used in forestry, which mainly includes land use classification and change monitoring, forest disaster monitoring, sparse vegetation detection, urban vegetation abundance estimation and estimation of inhomogeneous canopy parameters.