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首页> 外文会议>2011 Fourth International Symposium on Knowledge Acquisition and Modeling >Study on the Land Use and Cover Classification of Zhengzhou Based on Decision Tree
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Study on the Land Use and Cover Classification of Zhengzhou Based on Decision Tree

机译：基于决策树的郑州土地利用/覆被分类研究

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摘要

Based on the data of ETM+ multi-spectral remote sensing image obtained from Landsat-7, adopting the method of decision tree-based classification, the land use and present coverage situation of Zhengzhou city are classified in this article. On the foundation of the analysis of the information content of remote sensing image bands, the sample selection in field and the laboratory test, establish the classification rules of the nodes and then formed the color region graphs of land use and vegetation coverage. Correcting the classification results and alternating above operations, the precision of classification result produced by this method is about 94 percent. The result shows that decision tree-based classification method is better than the other traditional statistical classification methods, and it can deal with noise and lost information without depending on normal school data but not need the requirement of normal distribution. It has been proved that the decision tree-based classification method has obvious advantages, such as exact classification, efficient, definite classification criterion, intuitive classification structure controllable classification precision automated classification, etc.
机译：基于从Landsat-7获得的ETM +多光谱遥感图像数据，采用基于决策树的分类方法，对郑州市的土地利用和现状进行了分类。在分析遥感影像带信息内容，野外选样和实验室检测的基础上，建立节点分类规则，形成土地利用和植被覆盖度的彩色区域图。校正分类结果并交替进行上述操作，该方法产生的分类结果精度约为94％。结果表明，基于决策树的分类方法优于其他传统的统计分类方法，可以在不依赖于正常学校数据的情况下处理噪声和信息丢失，而又不需要正态分布的要求。实践证明，基于决策树的分类方法具有分类准确，分类效率高，分类标准明确，分类结构直观，可控分类精度高等优点。

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