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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Quantification of subpixel cover fractions using principal component analysis and a linear programming method: Application to the coastal zone of Roscoff (France)
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Quantification of subpixel cover fractions using principal component analysis and a linear programming method: Application to the coastal zone of Roscoff (France)

机译:使用主成分分析和线性规划方法对亚像素覆盖率进行量化:在Roscoff(法国)沿海地区的应用

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摘要

In this study, principal component analysis. and the linear programming method "affine algorithm" were jointly used to provide an unmixing method and to calculate fractions bounds of main seaweeds and intertidal components from mixed pixels. The method was tested using CASI airborne imagery data taken over the Roscoff coastal zone (Brittany, France). The contribution of the number of spectral bands used to identify many component types was also examined. Between four and six components can be distinguished depending on the spectral richness of the original image. The accuracy of fraction cover types was estimated by comparing calculated proportions with ground data. Whatever the number of bands and ground categories, the coefficient of determination R-2 was higher than 0.62. Much more information and more accurate results were obtained with 13 spectral bands (R-2 from 0.81 to 0.96). (C) Elsevier Science Inc., 1998. [References: 33]
机译:在本研究中,进行主成分分析。结合线性规划方法“仿射算法”提供一种解混方法,并根据混合像素计算主要海藻和潮间带组分的分界。使用从Roscoff沿海地区(法国布列塔尼)获得的CASI机载图像数据对该方法进行了测试。还检查了用于识别许多组件类型的光谱带数量的贡献。根据原始图像的光谱丰富度,可以区分出四个和六个分量。通过将计算出的比例与地面数据进行比较,可以估算出分数覆盖类型的准确性。无论频段和地面类别的数量如何,测定系数R-2均高于0.62。通过13个光谱带(R-2从0.81到0.96)获得了更多的信息和更准确的结果。 (C)Elsevier Science Inc.,1998年。[参考:33]

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