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基于Landsat TM数据估算雷竹林地上生物量

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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3.45 t·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13~25 t·hm-2,均值为19.52 t·hm-2.
Estimation of Aboveground Biomass of Phyllostachys praecox Forest Based on Landsat Thematic Mapper Image
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 of the PLS model has be improved through PLS-Bootstrap variable selection method, with a root mean square error ( RMSE ) of 3.45 t · hm-2 . The PLS model is an effective way of estimating AGB of Phyllostachys praecox forest in a large area. Most of Phyllostachys praecox in the forested area had AGB values between 13 and 25 t·hm2, and the average AGB density was 19. 52 t · hm-2.

Phyllostachys praecox forestaboveground biomassLandsat TM datapartial least squares regression

徐小军、周国模、杜华强、董德进、崔瑞蕊、周宇峰、沈振明

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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

临安市林业技术服务总站,临安,311300

雷竹林 地上生物量 Landsat TM遥感数据 偏最小二乘回归

国家林业局"948"引进项目国家自然科学基金浙江省科技厅项目浙江省重点科技创新团队

2008-4-49307006382008C120682010R50030

2011

林业科学
中国林学会

林业科学

CSTPCDCSCD北大核心
影响因子:1.272
ISSN:1001-7488
年,卷(期):2011.47(9)
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