| 基于主成分分析和人工神经网络的稻穗健康状态的高光谱识别 |
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| 引用本文： | 刘占宇,祝增荣,赵敏,王秀珍,黄敬峰.基于主成分分析和人工神经网络的稻穗健康状态的高光谱识别[J].浙江农业学报,2011,23(3):0. |
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| 作者姓名： | 刘占宇 祝增荣 赵敏 王秀珍 黄敬峰 |
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| 作者单位： | 1.杭州师范大学 遥感与地球科学研究院,浙江 杭州 311121;2.浙江大学 昆虫科学研究所, 浙江 杭州 310058;3.浙江省桐庐县农业技术推广中心,浙江 桐庐 311500;4.浙江大学 农业遥感与信息技术应用研究所,浙江 杭州 310058 |
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| 基金项目： | 国家重点基础研究发展规划(973)项目，国家公益性行业(农业)科研专项，国家自然科学基金，浙江省优先主题重大社会发展项目 |
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| 摘 要： | 水稻生长后期穗部遭受病虫危害会严重影响水稻产量,对不同健康状态的稻穗进行精准识别是采取病虫害防控措施和危害评估的依据。研究测定了健康稻穗、轻度、中度和重度危害稻穗及白穗的室内高光谱反射率,并着重分析了不同健康状态稻穗的原始光谱、对数光谱、一阶和二阶微分光谱特征。利用主成分分析方法获取了前述多种变换光谱的主分量,并以其为输入向量,利用学习矢量量化神经网络对多种健康状态稻穗进行分类。结果显示：原始光谱、对数光谱、一阶和二阶微分光谱的总体分类精度分别为75.3%, 74.7%, 91.6%和100%,Kappa系数分别为0.689, 0.682, 0.895和1.000。研究表明,运用高光谱遥感技术对稻穗健康状态进行识别是切实可行的。
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| 关 键 词： | 水稻 高光谱遥感 主成分分析 人工神经网络 |
Hyperspectral discrimination of different health conditions in rice panicles based on principal component analysis and artificial neural network |
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| LIU Zhan-yu,ZHU Zeng-rong,ZHAO Min,WANG Xiu-zhen,HUANG Jing-feng.Hyperspectral discrimination of different health conditions in rice panicles based on principal component analysis and artificial neural network[J].Acta Agriculturae Zhejiangensis,2011,23(3):0. |
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| Authors: | LIU Zhan-yu ZHU Zeng-rong ZHAO Min WANG Xiu-zhen HUANG Jing-feng |
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| Institution: | 1Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121,China; 2Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China; 3Tonglu Agro-Tech Extension Center, Tonglu 311500, China; 4Institute of Agricultural Remote Sensing and Information System Application, Zhejiang University, Hangzhou 310058, China |
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| Abstract: | The incidence of disease and insect stresses in rice panicles at the late growth stage had a negative impact on normal growth of panicles.Discrimination of health conditions in stressed rice panicles from healthy ones was the basis of plant protection measurements and yield assessment.Five kinds of health condition in rice panicles were classified in the study:no infection,light and moderate infection caused by rice glume blight disease,serious infection caused by rice false smut disease,and white headed pa... |
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| Keywords: | rice hyperspectral remote sensing principal component analysis artificial neural network |
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