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| 基于Landsat TM数据估算雷竹林地上生物量 | |
| 引用本文： | 徐小军,周国模,杜华强,董德进,崔瑞蕊,周宇峰,沈振明.基于Landsat TM数据估算雷竹林地上生物量[J].林业科学,2011,47(9). |
| 作者姓名： | 徐小军 周国模 杜华强 董德进 崔瑞蕊 周宇峰 沈振明 |
| 作者单位： | 1. 浙江农林大学环境与资源学院,浙江省森林生态系统碳循环与固碳减排重点实验室,临安,311300 2. 浙江农林大学环境与资源学院,浙江省森林生态系统碳循环与固碳减排重点实验室,临安,311300;亚热带森林培育国家重点实验室培育基地,临安,311300 3. 临安市林业技术服务总站,临安,311300 |
| 基金项目： | 国家林业局948项目(2008-4-49); 国家自然科学基金项目(30700638); 浙江省科技厅项目(2008C12068); 浙江省重点科技创新团队(2010R50030) |
| 摘 要： | 结合Landsat TM遥感数据和雷竹林样地调查数据,采用偏最小二乘回归法(PLS)建立雷竹林地上生物量估算模型,利用该模型估算临安市雷竹林地上部分生物量。结果表明:雷竹单株地上部分生物量与胸径及雷竹林地上部分生物量与株数之间都呈极显著相关(P<0.01);通过PLS-Bootstrap法筛选自变量能够提高模型精度;模型预测的雷竹林地上生物量均方根误差为3.45t·hm-2,满足大范围估算的精度要求;临安市雷竹林地上生物量为13～25t·hm-2,均值为19.52t·hm-2。 |
| 关 键 词： | 雷竹林 地上生物量 Landsat TM遥感数据 偏最小二乘回归 |
Estimation of Aboveground Biomass of Phyllostachys praecox Forest Based on Landsat Thematic Mapper Image |
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| Xu Xiaojun,Zhou Guomo,Du Huaqiang,Dong Dejin,Cui Ruirui,Zhou Yufeng,Shen Zhenming.Estimation of Aboveground Biomass of Phyllostachys praecox Forest Based on Landsat Thematic Mapper Image[J].Scientia Silvae Sinicae,2011,47(9). | |
| Authors: | Xu Xiaojun Zhou Guomo Du Huaqiang Dong Dejin Cui Ruirui Zhou Yufeng Shen Zhenming |
| Institution: | Xu Xiaojun1 Zhou Guomo1,2 Du Huaqiang1,2 Dong Dejin1 Cui Ruirui1 Zhou Yufeng1 Shen Zhenming3(1.School of Environment and Resource,Zhejiang Agriculture and Forestry University Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration Lin'an 311300,2.Nurturing Station for State Key Laboratory of Subtropical Silviculture Lin'an 311300,3.Forestry Technical Service Station of Lin'an Lin'an 311300) |
| Abstract: | Based on data collected with Landsat Thematic Mapper(TM),a remote sensing technique,and a field survey,a model established with the partial least squares(PLS) regression was used to estimate aboveground biomass(AGB) of Phyllostachys praecox forest in Lin'an City,Zhejiang Province.Results showed that AGB of individual Phyllostachys praecox was significantly correlated with diameter at breast height and AGB of Phyllostachys praecox forest was significantly correlated with culms density.The predicted accuracy ... |
| Keywords: | Phyllostachys praecox forest aboveground biomass Landsat TM data partial least squares regression |
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