光谱特征空间(Spectral 光谱特征空间(Spectral Feature Space)：所有波段的亮度 Space)： 轴构成的直角坐标空间，同类地物具有聚类(Clustering)的 效应。
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结合粗糙集理论和遥感数据中地物光谱特征空间分布信息，提出了一种基于光谱特征邻域的容差粗糙集分类方法，用来处理卫星遥感数据分类中的不确定性问题。
Based on the spectral feature neighborhood, this paper proposes a tolerant rough set classification method to handle the uncertainty in the process of satellite remote sensing data classification.
遥感数据源在信息提取和识别的过程中主要表现为三大特征：空间特征、光谱特征和时间特征。
During the information detection and discrimination, the remote sensed data always represents three important characters: space character, spectral character and time character.
通过光谱特征选择及空间降维处理，建立了判别函数，确定了判别规则。
The critical function and critical rules based on the spectrum characteristic selection and the process of spatial dimensional reduction were established.
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