Remote Sensing Experts Classification System Applying in the Land Use Classification in Guangzhou City

H. Cui, Huaisui Qian, Le-xiang Qian, Ying Li
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引用次数: 1

Abstract

With an increasingly rich of the remote sensing data, how to extract meaningful surface information from the mass of remote sensing data has become a problem pressed for solution. Using the experts classification method, digital elevation model and the generated slope and aspect information as expert-assisted classification parameters, land use types of Guangzhou city are classified. The results show that the participation of more variable information such as elevation and slope can prevent the frequent occurrence phenomenon of same object with different spectra and different objects with same spectrum in the remote sensing classification effectively eliminate the impact of terrain. Consequently, effectively improve the accuracy of remote sensing image classification. Both accuracy of types and precision of the area, experts classification has the higher precision than the maximum likelihood supervised classification, provides an effective way to the land use classification for the complex terrain region.
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遥感专家分类系统在广州市土地利用分类中的应用
随着遥感数据的日益丰富,如何从海量遥感数据中提取有意义的地表信息已成为一个亟待解决的问题。采用专家分类方法,利用数字高程模型和生成的坡向信息作为专家辅助分类参数,对广州市土地利用类型进行了分类。结果表明,高程、坡度等更多变量信息的参与,可以防止遥感分类中同一物不同光谱和不同物同一光谱频繁发生的现象,有效消除地形的影响。从而有效地提高了遥感图像分类的精度。无论是类型的精度还是面积的精度,专家分类都比最大似然监督分类具有更高的精度,为复杂地形区域的土地利用分类提供了一种有效的方法。
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