Position: Home > Articles > Application of a Hybrid Classification Technique on the Forest Classification
Sichuan Forestry Exploration and Design
2004
(2)
60-64
一种遥感混合分类算法及其在森林分类中的应用
作 者：
杨永恬;田昕;冯仲科
单 位：
北京林业大学
关键词：
IGSCR;森林分类;分类精度
摘 要：
基于监督分类和非监督分类方法相结合的混合分类方法在森林非森林的识别方面有很好的识别效果 ,探讨了一种遥感混合分类算法 ( IterativeGuided Spectral Class Rejection)。首先对 IGSCR的算法理论进行了阐述 ,然后利用 IGSCR分类算法对同一地区多时相遥感影像进行复合的影像进行森林分类实验。通过与最大似然法的对比实验表明 ,IGSCR分类方法将非监督分类方法所具有的自动对具有相同光谱特征类别进行集群的能力 ,辅助于训练样本的获取 ,可以有效降低因人工判断类别光谱纯度不准确而引起的类别样本光谱混杂问题 ,因此能在一定程度上提高分类精度 ,改善分类效果
译 名：
Application of a Hybrid Classification Technique on the Forest Classification
作 者：
YANG Yong tian,TIAN Xin,FENG Zhong ke (Beijing Forestry University ,Beijing,100083,China)
关键词：
IGSCR, Forest Classification,Classification Accuracy
摘 要：
Based on the good classification results to the identification of the forest and non forest using the blending method of the combination of unsupervised and supervised method, the “Iterative Guided Spectral Class Rejection” classification method was probed. First the theory of the “Iterative Guided Spectral Class Rejection” algorithm was described. Then we developed the algorithm to make a classification experiment using a multi temporal composite image in the same site. Compared with the maximum likelihood classification method, the “Iterative Guided Spectral Class Rejection”algorithm can effectively reduce the problem of training data miscellany caused by the human factors such as distinguishing inaccurateness of the spectral purity using the automatic cluster ability to the same spectral character sort of the unsupervised method, assisting with the acquirement of the training data. Thus, the IGSCR algorithm can effectively increase the classification accuracy.
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遥感混和分类算法及其在森林分类中的应用 [杨永恬, 田昕, 冯仲科, 吴发盛, 李树彦] 长江大学学报(自科版)农学卷 2004 (4)
