基于近红外波段玉米叶绿素含量最佳预测模型研究

为了进一步探究近红外波段玉米光谱反射率与其叶绿素含量之间的关系，笔者采用线性和非线性法对玉米叶绿素含量与近红外波段光谱反射率及植被指数之间的关系进行分析，建立叶绿素含量最佳预测模型。结果表明：在近红外波段，光谱反射率与玉米叶绿素含量的相关性较大；叶绿素含量与RVI(R1001/R760)、RSI(R765/R720)、NDVI(R990-R760)/(R760+R990)、NDSI(R813-R763)/(R813+R763)、CCI(D794/D763)等植被指数均达极显著相关，其中与NDVI的相关性最大，为0.91。基于近红外波段的植被指数建立玉米叶绿素含量预测模型中，采用RVI、RSI、NDVI、NDSI所建的二次多项式模型其决定系数R2均高达0.75以上。采用990、760nm处的归一化植被指数NDVI建立的二次多项式为玉米叶绿素含量最佳预测模型，其具有最大决定系数(R2=0.855)，较小RMSE(2.433)和RE%(0.61%)，为利用高光谱信息反映玉米生长状况的叶绿素信息提供了基础。

Optimum Prediction Model of Maize Leaf Chlorophyll Content Based on Near-infrared Band

In order to further explore the relationship between near-infrared band reflectance of maize and its chlorophyll content, the author analyzed the relationship between chlorophyll content of maize and nearinfrared band reflectance and vegetation index by linear and non- linear methods to establish the optimum chlorophyll content prediction model. The results showed that the correlation spectral reflectance and chlorophyll content was great at near-infrared band; chlorophyll content had highly significant correlation with RVI (R1001/R760), RSI (R765/R720), NDVI (R990-R760)/(R760+R990), NDSI (R813-R763)/(R813+R763), CCI (D794/D763) and so on, and NDVI had the biggest correlation index (0.91). Determination coefficient R2 of all quadratic polynomial adopted RVI、 RSI、 NDVI、 NDSI reached 0.75 in the maize chlorophyll content prediction model based on nearinfrared band vegetation index. The quadratic polynomial which based on NDVI at 990, 760 nm was the optimum maize chlorophyll content prediction model, it had the biggest determination coefficient (R2=0.855) and lesser RMSE (2.433) and RE% (0.61%). All those results could offer basis for using spectral information to reflect chlorophyll content in maize growth condition.