基于Landsat8 OLI多光谱数据和内蒙古兴安盟地区189块山杏、柠条灌木林实测样地数据,利用多元逐步回归法建立地上碳储量遥感模型,并对模型的预估精度进行了分析。结果表明:选取包括单波段、波段组合、缨帽变换、植被指数及主成分分析共5组27个特征变量,通过分析27个特征变量与灌木林地上碳储量的Pearson相关性,进行特征变量的优化选取并建立模型。天然山杏、人工山杏和人工柠条3种灌木类型地上碳储量遥感模型的决定系数分别为0.61,0.86,0.74,预估精度分别为71%,77%,73%。优化的3种遥感模型可以应用到内蒙古范围内天然山杏、人工山杏和人工柠条林地上碳储量评估工作中。
In Xing'an League of Inner Mongolia,we made use of Landsat8 OLI imagery and a survey of 189 plots in Armeniacasibirica,Caraganakorshinskii shrubberies,and multiple regression to establish remote sensing ground carbon storage model and analyze the prediction accuracy of the model.The results show that 27 independent variables were selected out,including single band,band combination,tasseled cap transformation,vegetation index and principal components.The Pearson correlation analysis between the 27 independent variables and shrubbery carbon storage has been calculated to select the better characteristic variables.The coefficients of determination of natural Armeniacasibirica,artificial Armeniacasibirica and artificial Caraganakorshinskii remote sensing above ground carbon storage model are 0.61,0.86 and 0.74 respectively;The prediction accuracy values of the model are 71%,77% and 73% respectively,the optimization of three kinds of remote sensing models can be applied to a range within the Inner Mongolia natural Armeniacasibirica,artificial Armeniacasibirica and artificial Caraganakorshinskii above ground carbon stocks assessment.
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