夏玉米叶面积指数的高光谱遥感植被指数法研究

Study on Colony Leaf Area Index of Summer Maize by Remote Sensing Vegetation Indexes Method

通过不同品种夏玉米在不同供氮水平下的田间试验,测定夏玉米冠层在不同时期的光谱反射率及对应的群体叶面积指数(LAI),综合分析10个常见光谱植被指数与夏玉米LAI的相关性及预测性。结果表明,光谱植被指数的预测性在夏玉米喇叭口-吐丝期最佳,预测性主要依赖于LAI的整体变化,结合不同品种、不同生育时期和氮肥处理的试验资料对其预测性进行检验,说明光谱植被指数能准确地预测LAI。尤其是近红外与绿光波段的比值(R810/R560)与LAI呈显著的指数关系,不受品种类别、生育时期和氮肥水平的影响,回归模型为LAI=0 765e0 2637R810/R560。利用样本A和B对R810/R560的预测性进行综合检验,表明模拟值与实测值之间符合度较高,平均R2=0 9573 ,估算的平均RMSE为0 0365,精确度和准确度平均值分别为95 63%和98 47%。

The spectral reflectances and colony leaf area index (LAI) of summer maize were measured in field and indoor respectively under different varieties and nitrogenous levels.In order to estimate LAI and establish the best estimation model of it,ten normal vegetation indexes(VI) were compared to find out the best one.The results indicated that the estimation of VI for assessing LAI was the best one from bell stage to silking stage of summer maize,and mainly depended on the whole variation in LAI.When the estimation of VI was tested with the independent data for different varieties and different nitrogenous levels,the VI could accurately forecast the variation in LAI.Especially, R_(810)/R_(560) was remarkably correlated with LAI in exponent form,which couldn′t be affected by the varieties,growth durations and nitrogenous levels.The regression model was as follows:LAI= 0.765e^(0.2637R_(810)/R_(560)).The model was synthetically tested with sample A and B respectively and the assessment average R^2,precision and accuracy were about 0.9573^(**),95.63%and 98.47%with average RMSE of 0.0365 respectively.