机载高光谱数据提取冬小麦冠层叶绿素含量的模型分析及验证

遥感提取叶绿素含量的方法是精准农业的重要研究方向之一，但是如何用冠层光谱数据有效地提取叶绿素含量仍然是一个难点。本文用光谱指数TCARI和OSAVI的组合建立提取冬小麦冠层叶绿素含量的关系式，并使用实验田获取的冬小麦冠层光谱以及与之同步的机载高光谱传感器OMIS数据进行了验证。通过误差分析讨论了该方法用于遥感高光谱数据时需要注意的问题，表明大气校正的精度，传感器的信噪比以及波段中心的漂移是模型反演精度的主要制约因素。

Model Analysis and Validation by Using Airborne Hyperspectral Remote Sensing Data to Extract Winter Wheat Canopy Chlorophyll Content

Using remote sensing data to extract chlorophyll content is one of the important research directions of precision agriculture, but it is still difficult to effectively get the chlorophyll content using canopy spectral data. In this paper the spectral indices TCARI and OSAVI are combined to develop a relationship of retrieving the winter wheat canopy chlorophyll content and this relationship is validated by field wheat spectra and in situ airborne OMIS data. Error analysis is discussed about the problems when this relationship is applied to the hyperspectral remote sensing data. It is showed that the accuracy of atmospheric correction, the SNR of the sensor and the shift of band center are the main constrains of the model.