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The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

机译:最小二乘混合模型可生成从遥感多光谱数据中得出的分数图像

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摘要

Constrained-least-squares (CLS) and weighted-least-squares (WLS) mixing models for generating fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure, i.e. the fraction of inferred shade in the pixel is related to different eucalyptus ages.
机译:提出了约束最小二乘(CLS)和加权最小二乘(WLS)混合模型,用于生成从遥感多光谱数据中导出的分数图像。进行了考虑像素内的三个组成部分的实验:桉树,土壤(林下)和阴影。通过考虑性能和计算机时间,比较了从这两种方法得出的生成的阴影分数图像(阴影图像)。得出的阴影图像与观察到的森林结构变化有关,即,像素中推断出的阴影部分与不同的桉树年龄有关。

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