棉花全生育期叶片SPAD值的遥感估算模型

Remote sensing estimation model of cotton leaf SPAD value at the whole growth period

叶绿素含量是评估棉花生长状况的重要参数,估算叶绿素含量对于棉花生长监测具有重要意义。以渭北旱塬区种植的棉花为试验材料,测量全生育期棉花叶片SPAD值与冠层反射率光谱,将原始高光谱反射率、一阶微分光谱反射率、不同波段组合的遥感光谱参数分别与SPAD值做相关性分析,用传统回归分析方法构建五种重要光谱参数的SPAD值预测模型,同时,采用PLSR方法建立全生育期SPAD值的估算模型。最后对模型进行检验,筛选出精度最高的模型。建模结果表明,基于多种光谱参数的全生育期PLSR预测模型精度最高、预测效果最好,估算模型的决定系数R^2为0.733,验证模型R^2为0.737。PLSR方法建立的多光谱参数的SPAD值估算模型预测效果显著,利用高光谱技术对棉花SPAD值进行监测,可为全生育期棉花长势遥感监测提供依据。

Chlorophyll concentration is an important parameter to evaluate cotton＇ s growth conditions. So it is sig-nificant to estimate chlorophyll content for monitoring of cotton growth information. The materials of this research was the cotton in field in Wei-bei plateau region. Firstly the SPAD value was measured with SPAD - 502 in field, and the spec-tral reflectance of canopy was measured with SVC Handheld spectrometer. Then the correlation was analyzed between the SPAD value and single narrow band raw reflectance, or the first derivative spectral reflectance, or spectral indices com-bined from different band. The prediction model was established with 5 representative spectral indices. At the same time, the simulation model of remote sensing of canopy SPAD value at the whole growth period in cotton was estimated based on PLSR method. Finally, the highest precision model was filtered out by testing. The result showed that the model based on various spectral indices with PLSR method obtained the most satisfing results for the estimation of chlorophyll concen-tration, R2 of the estimation model is 0.733, R2 o f the ve r ific a tio n model was up to 0.737. The remote sensing models at the whole growth stage in cotton built with PLSR method based on important spectral indices provides a basis for moni-toring cotton crop growing trend and forecasting production with reliable forecast.