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    王蕾, 黄华国, 张晓丽, 骆有庆, 安树杰. 基于知识规则的马尾松林遥感信息提取技术研究[J]. 北京林业大学学报, 2007, 29(3): 124-130. DOI: 10.13332/j.1000-1522.2007.03.020
    引用本文: 王蕾, 黄华国, 张晓丽, 骆有庆, 安树杰. 基于知识规则的马尾松林遥感信息提取技术研究[J]. 北京林业大学学报, 2007, 29(3): 124-130. DOI: 10.13332/j.1000-1522.2007.03.020
    WANG Lei, HUANG Hua-guo, ZHANG Xiao-li, LUO You-qing, AN Shu-jie. RS information extraction techniques of Pinus massoniana forests based on knowledge rules[J]. Journal of Beijing Forestry University, 2007, 29(3): 124-130. DOI: 10.13332/j.1000-1522.2007.03.020
    Citation: WANG Lei, HUANG Hua-guo, ZHANG Xiao-li, LUO You-qing, AN Shu-jie. RS information extraction techniques of Pinus massoniana forests based on knowledge rules[J]. Journal of Beijing Forestry University, 2007, 29(3): 124-130. DOI: 10.13332/j.1000-1522.2007.03.020

    基于知识规则的马尾松林遥感信息提取技术研究

    RS information extraction techniques of Pinus massoniana forests based on knowledge rules

    • 摘要: 由于遥感信息提取精度的限制,使得遥感技术在林业领域的应用受到了制约.为了提高林业遥感信息提取精度,该文对遥感信息提取的3个关键技术环节即训练样区的选取、分类特征波段的选择及分类器的训练进行了研究,建立了基于知识规则的信息提取方法和流程.应用该方法,以浙江省富阳市为研究区,进行了马尾松林信息提取,精度达到了80.5%,比最大似然法提高了近20%.实例研究表明,该信息提取方法较为有效,尤其是在树种信息提取方面具有一定的研究和应用潜力,同时也为浙江地区应用遥感技术研究虫害提供了一定的技术支持.

       

      Abstract: The application of remote sensing(RS) technique in forestry industry has been restricted by the low precision of the information extraction.In order to improve the precision,three key techniques of the information extraction were studied,including selecting training samples,selecting classification bands and training classifier.Then the method and process of information extraction based on knowledge rules were built.This method was applied and validated in Fuyang City,Zhejiang Province,and the information extraction precision was up to 80.5%, which was 20% higher than that of MLC(maximum likelihood classification) method.The results show that this method is effective in the tree species information extraction and there is still research potential.This method can provide technique support for RS application on forest pest studying of Zhejiang Province.

       

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