三维高光谱NPLS模型用于冬小麦估产的初步研究

Study on NPLS Model with Three-Dimensional Hyperspectrum for Assessing Per-Mu-Yield of Winter Wheat

以35个实验小区,8个生育期的冬小麦田间测量冠层反射高光谱组成三维数据信息阵,采用多维偏最小二乘(multiway partial least squares,NPLS)算法建立了冬小麦亩产量估产模型。模型用于对13个实验小区产量预测分析,预测值与实际值的相关系数r为0.936 6,平均相对误差为4.44%,说明模型的预测效果较好,对实际的估产工作有一定的指导意义。

The present study piled a cube array with the winter wheat＇s cap reflection hyperspectra sampled from 35 experimental districts during 8 growth periods, and then used a multiway partial least squares （NPLS） algorithm to establish a model to assess the per-mu-yield of winter wheat. The model was used to predict the per-mu-yields of other 13 experimental districts. The correlation coefficient of predicted and actual values was 0. 936 6, and the mean relative error was 4.44%. These results showed a good prediction of the model. The study has guiding meaning to actual yield assessment.