Wang Yuan, Huang Jing-Feng, Wang Fu-Min, Liu Zhan-Yu
Institute of Agricultural Remote Sensing and Information Application, Huajiachi Campus, Zhejiang University, Hangzhou 310029, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2008 Feb;28(2):273-7.
An experiment was designed to determine whether nitrogen concentrations could be predicted from reflectance (R) spectra of rape leaves in laboratory, and, if so, whether the predictive spectral features could be correlated with nitrogen concentration of simple canopies of rape. The best predictors for nitrogen in leaves appeared with first-difference transformations of R, and the bands selected were similar to those found in other studies. Shortwave infrared bands were best predictors for nitrogen. In the shortwave infrared region, however, the absolute differences in reflectance at critical bands were extremely small, and the bands of high correlation were narrow. High spectral and radiance resolution are required to resolve these differences accurately. Variability in canopy reflectance in shortwave infrared region was at least an order of magnitude beyond that necessary to detect signals from chemicals. The variability in first-difference R and log 1/R on canopy scales were related to the arrangement of trees with respect to direct solar radiation, instrument noise, leaf fluttering, and small change in atmospheric moisture. The first-difference of reflectance R based regressions prediction of nitrogen concentration at canopy level gets a good fitness.
设计了一项实验，以确定在实验室中能否根据油菜叶片的反射率（R）光谱预测氮浓度，若可以，预测光谱特征是否与油菜单冠层的氮浓度相关。叶片中氮的最佳预测指标出现在R的一阶差分变换中，所选波段与其他研究中发现的波段相似。短波红外波段是氮的最佳预测指标。然而，在短波红外区域，关键波段的反射率绝对差异极小，且高相关波段很窄。需要高光谱和高辐射分辨率才能准确分辨这些差异。短波红外区域冠层反射率的变异性至少比检测化学物质信号所需的变异性高一个数量级。冠层尺度上一阶差分R和对数1/R的变异性与树木相对于直射太阳辐射的排列、仪器噪声、叶片飘动以及大气湿度的微小变化有关。基于反射率R一阶差分的冠层水平氮浓度回归预测具有良好的拟合度。
