| 基于径向基函数的神经网络对森林碳空间分布的模拟 |
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| 引用本文： | 汪少华,张茂震,祁祥斌,赵平安,陈金星,朱孟涛.基于径向基函数的神经网络对森林碳空间分布的模拟[J].西南林学院学报,2011,31(4):12-17,F0003. |
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| 作者姓名： | 汪少华 张茂震 祁祥斌 赵平安 陈金星 朱孟涛 |
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| 作者单位： | 1. 浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室，浙江临安311300；浙江农林大学环境科技学院，浙江临安311300
2. 山东临沂市河东区林业局,山东临沂,276034 |
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| 基金项目： | 国家自然科学基金项目(30972360)资助；浙江省重大科技专项重点农业项目 |
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| 摘 要： | 利用径向基神经网络,结合森林资源清查的930个样地调查数据和对应的TM影像数据,选取与森林生物量相关性较大的3个植被指数TM4/57、ARVI和KT2作为神经网络的输入变量,对临安市森林碳储量的空间分布进行模拟。结果显示,利用径向基神经网络较好地重建了森林碳储量空间分布和变化,模拟结果与样地实测值间的一致性好,为区域森林碳储量的估测研究提供了方法支持。
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| 关 键 词： | 森林碳 径向基神经网络 森林资源清查 TM影像 |
Modeling the Spatial Distribution of Forest Carbon Storage by Neural Network Based on Radial Basis Function |
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| WANG Shao-hua,ZHANG Mao-zhen,QI Xiang-bin,ZHAO Ping-an,CHEN Jin-xing,ZHU Meng-tao.Modeling the Spatial Distribution of Forest Carbon Storage by Neural Network Based on Radial Basis Function[J].Journal of Southwest Forestry College,2011,31(4):12-17,F0003. |
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| Authors: | WANG Shao-hua ZHANG Mao-zhen QI Xiang-bin ZHAO Ping-an CHEN Jin-xing ZHU Meng-tao |
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| Institution: | 1.Zhejiang Provincial Key Laboratory of Forest Ecosystem Carbon Cycling,Carbon Sequestration and Emission Reduction,Zhejiang A＆F University,Lin′an Zhejiang 311300,China;2.College of Environmental Science and Technology,Zhejiang A＆F University, Lin′an Zhejiang 311300,China;3.Forestry Bureau of Hedong District,Linyi Municipality,Linyi Shandong 276034,China) |
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| Abstract: | By means of applying the radial-basis-function-neural-network（RBFnn） method and integrated with the field survey data from 930 sample plots obtained by the forest inventory and the corresponding TM images,the spatial distribution of the forest carbon storage of Lin′an Municipality was simulated by taking 3 three vegetation indices,i.e.,TM4/57,ARVI and KT2 as the input variables.The results showed the radial-basis-function-neural-network（RBFnn） method could accurately generate the spatial distribution and the variation of forest carbon storage,and there was a very good consistency between the simulated results and the data obtained from the field survey,which provided the predictive studies of forest carbon storage with methodological reference. |
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| Keywords: | forest carbon radial basis neural network forest resource inventory TM images |
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