干旱胁迫下油菜含水率的高光谱遥感估算研究

Study on Estimation Model for Rape Moisture Content under Water Stress Based on Hyperspectral Remote Sensing

[目的]研究基于光谱分析技术进行油菜含水率定量分析的有效方法。[方法]采用区间分段逐步回归法提取特征波长,在此基础上,建立了油菜含水率的定量分析模型,对不同干旱胁迫下油菜样本的光谱数据进行分析。[结果]960、1 450、1 650 nm波段的光谱反射率与油菜含水率呈极显著相关。油菜含水率模型预测值与实测值的相关系数为0.87,模型的均方根误差(RMSE)为4.57。[结论]该方法能够准确地提取光谱特征,提高模型的预测精度。

[Objective] The aim of the study was to seek a good anesthetic that using spectral analysis to quantitatively analyze the rape water stress condition.[Method]Region stepwise regression was proposed to select the characteristic wavelength of rape moisture content and establish the model between the moisture content and the spectral reflectance at characteristic wavelength of rape.[Result]From the spectral datum of rape samples under different water levels,it was found that the linear relationships between moisture content of rape and spectral reflectance value at 960,1 450 and 1 650 nm were very notable.The correlation coefficient between the predict value and the measured value was 0.87,the RMSE was 4.57.[Conclusion]The results showed that the method of stepwise regression could select the characteristic wavelengths of rape moisture content accurately and enhance model forecast precision.