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基于不同模型的土壤有机质含量高光谱反演比较分析/Comparative Analysis of Soil Organic Matter Content Based on Different Hyperspectral Inversion Models[J]
Authors
LUAN Fu-ming
WANG Fang
+13 more
XIONG Hei-gang
ZHANG Fang
ZHANG Xiao-lei
中国科学院大学,北京100049
中国科学院新疆生态与地理研究所,新疆乌鲁木齐830011
北京联合大学应用文理学院,北京100083
张小雷
张芳
新疆大学资源与环境科学学院,新疆乌鲁木齐,830046
新疆大学资源与环境科学学院,新疆乌鲁木齐830046
栾福明
熊黑钢
王芳
Publication date
1 January 2013
Publisher
Abstract
以新疆奇台县为研究区域,选取该县40个土壤样本,采用多元线性逐步回归法和人工神经网络法两种方法分别建立了土壤有机质含量的反演模型,并对模型进行了检验.结果发现:不同模型的精度值各异,其拟合效果从高到低依次为人工神经网络(ANNs)集成模型>单个人工神经网络(ANNs)模型>多元逐步回归(MLSR)模型.人工神经网络的线性和非线性逼近能力较强,而其集成模型作为提高反演模型精度的重要手段,相关系数高达0.938,均方根误差和总均方根误差最小,分别仅为2.13和1.404,对土壤有机质含量的预测能力与实测光谱非常接近,分析结果达到了较实用的预测精度,为最优拟合模型
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Last time updated on 29/11/2016