提出了基于支持向量机(Support Vector Machine, SVM) 的遥感影像分类方法, 结合空间特征等信息, 对IKONOS高空间分辨率影像进行分类, 实施对生态公益林的监测, 并将此分类方法与传统分类方法进行比较分析。研究结果表明, 基于SVM的遥感分类方法能够有效解决分类效果破碎、精度不高等问题, 而且在学习速度、自适应能力、可表达性等方面具有优势。
This paper deals with the RS image classification based on the SVM method, using space characteristic information for classification of IKONOS high spatial resolution images and monitoring of public w elfare forests.Analy sis was conducted on comparison of this method with tradition method. The resultshow s that the RS image classification based on the SVM method can solve the image classification fragmentation, low accuracy etc, and has advantage in study speed, orientation abili ty and expression, etc.The aim of this paper is to discuss a method to inquire into the classification method of public welfare forests with high spatial resolution RS image and providing theoretical basis and data support for the development of forestry information netw ork and “digi tal forestry”.
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