• ISSN 1008-505X
  • CN 11-3996/S

基于主成分回归分析的土壤有机质高光谱预测与模型验证

Application of hyperspectral data for soil organic matter estimation based on principle components regression analysis

  • 摘要: 在室内条件下,利用ASD2500高光谱仪测定了风干土壤样品的光谱。通过相关分析对土壤有机质(SOM)光谱敏感波段进行了初步筛选;利用逐步回归分析和主成分回归(PCR)分析等统计方法进行了显著性变量筛选、共线性诊断、数据转换等处理;最终建立了东北黑土SOM回归预测模型。模型所选的波段为均位于近红外波段。经验证,模型预测值与实测值的决定系数R2=0.840,总均方根差RSME=0.226。

     

    Abstract: Soil organic matter (SOM) content is an important indicator of soil fertility. It provides important information for soil digital management and resource evaluation if SOM can be estimated using hyperspectral technology. In this experiment, Visible-NIR spectral reflectance of soil samples was measured by using an ASD2500 device. The sensitive bands for SOM estimation were initially determined by applying correlation analysis. Furthermore, the processings including the selection of significant variables, collinearity diagnostics and data transformation were carried out by using stepwise regression analysis and principle components regression (PCR) analysis. The predicting model for SOM estimation was developed for black soil in northeast China. The validation results showed that the model was effective and practicable (R2=0.840, RSME=0.226)

     

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