This paper conveys the application of genetic algorithms (GA) which are used to improve unsupervised training and thereby increase the classification accuracy of remotely sensed data.
本文将遗传算法(GA)应用于非监督训练，提高了遥感数据的分类精度。
This paper presents the classification of saline soil method, based on knowledge discovery and decision supporting rule base systems using remotely sensed data and GIS.
提出了基于知识发现和决策规则基础的盐碱地GIS和遥感分类的方法。
The invention relates to a supervised classification method of multi-class hyperspectrum remotely sensed data, which comprises the following steps: (1), reading the hyperspectrum data;
一种高光谱遥感数据多类别监督分类方法，包含以下步骤：（1）读入 高光谱数据；
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