remote sensing classification method 遥感分类方法
hyperspectral remote sensing classification 高光谱遥感分类
validation on remote sensing classification 遥感分类验证
remote sensing image classification 遥感影像分类
Remote sensing information classification 遥感信息分类
hyperspectral remote sensing image classification 高光谱遥感影像分类
classification of remote sensing data 遥感影像分类
Support Vector Machines(SVM) is a potential hyperspectral remote sensing classification method because it is advantageous to deal with problems with high dimensions, small samples and uncertainty.
支持向量机因其适用高维特征、小样本与不确定性问题的优越性，是一种极具潜力的高光谱遥感分类方法。
The optimum selection of bands and its combinations in remote sensing classification and the method for expanding feature space are presented.
本文结合第四纪沉积物类型的划分，讨论了遥感分类中最佳波段和波段组合的选取以及特征空间的扩充方法。
Concluded that the object-oriented classification than the pixel-based classification more precise, more suitable for high-resolution remote sensing classification.
得出结论，面向对象分类法比基于像元的分类法精度更高，更适合于高分辨率遥感分类。
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