基于SPOT-5的森林蓄积量估测模型研究  

A model of estimating forest volume based on SPOT-5

作　　者：涂云燕[1] 张盼盼[1] 

机构地区：[1]国家林业局昆明勘察设计院,云南昆明650216

出　　处：《林业建设》2015年第4期61-65,共5页Forestry Construction

摘　　要：【目的】利用遥感和地形信息分析其与地面样地蓄积量的相关关系,探讨基于遥感和地学信息的森林蓄积量遥感估测方法。【方法】以样地蓄积量作为因变量,以SPOT5图像各波段、海拔、坡度及郁闭度为自变量,建立主成分回归、偏最小二乘回归、逐步回归模型。并从模型拟合效果、样本配对系数、模型适用性进行了比较分析。【结果】在同一自变量标准与估测精度保证的情况下,综合考虑拟合效果、估测值与实测值样本配对相关系数及模型适用性,以逐步回归模型最优。【结论】将逐步回归模型反演整个研究区得到估测蓄积量为33197465.0m3,野外实测值为31813463.0m3。[ Objective ] Analysed the relationship between remote sensing and geosciences information and the ground sample volume,investigated forest volume estimation method based on remote sensing and geosciences information. [ Method ] Taked sample volume as the dependent variable, each band of SPOT-5 image, elevation, slope and canopy density as independent variables,established the principal component regression, partial least squares, stepwise regression model,finally comparative and analysis which is better from fitting results, sample matching coefficient and applicability of model. [ Result ] Under the circumstances of the same standard of independent variables and ensure the estimation accuracy, stepwise regression is superior to principal component regression and partial least squares regression from the fitting results, the estimation value and the measured values sample paired correlation coefficient and the model applicability. [ Conclusion ] Using the regression model to estimate regional,the result is 33197465 m3,and field measured value is 31813463m3.

关 键 词：自变量间多重相关性 主成分回归 偏最小二乘 逐步回归 

分 类 号：S758.51[农业科学—森林经理学]