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- W1533420114 abstract "木薯作为重要的非粮能源作物,因其种植分散、与易混淆作物缺乏生长时相差,从而导致其种植分布信息难以正确获取,一直是困扰木薯乙醇资源正确评估的技术问题。该研究以广西壮族自治区武鸣县为研究区,应用高分辨率RapidEye影像数据,探讨利用面向对象分类方法合理提取木薯种植面积及其空间分布信息。研究表明,将归一化植被指数(NDVI)和数字高程数据(DEM)应用于遥感影像的多尺度分割,并结合基于隶属度函数和阈值的面向对象分类方法,提取木薯种植面积的精度达85%,分类精度(以Kappa系数表示)为0.9。相比最大似然监督分类方法和未辅以NDVI/DEM的面向对象分类方法,该方法的总精度分别提高了5%和12%,Kappa系数分别提高了0.2和0.3。因此,NDVI和DEM数据参与影像分割的面向对象的信息提取方法,可以有效地提高遥感图像分类的精度,并为提取种植分散、与相关植被时相差异小的作物的空间分布提供了有效的技术借鉴。" @default.
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- W1533420114 date "2015-01-01" @default.
- W1533420114 modified "2023-09-23" @default.
- W1533420114 title "辅以NDVI／DEM的面向对象木薯提取方法研究——以广西壮族自治区武鸣县为例" @default.
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