基于Hyperion数据的南四湖叶绿素浓度反演研究

通过对2005年5月7日南四湖Hyperion高光谱影像的几何纠正和6S模型辐射校正,以及水体光谱数据分析,对22个水体样点原始光谱数据分别采用归一化处理和包络线消除处理后,以波段比值数据构建叶绿素浓度反演模型,选取相关系数最大的反演模型,获得南四湖叶绿素浓度的空间分布图。研究表明,包络线消除法能很好地去除水体的光谱曲线背景影响,突出光谱曲线的吸收和反射特征,与归一化处理相比,反演模型的相关系数都有很大提高。R700/R560波段比值数据构建的模型相关性最高,相关系数为0.834,可用于叶绿素浓度反演研究。

Regression of Chlorophyll Content Based Hyperion Data in Nansi Lake

Based on geometry correction using ERDAS software and radiation correction using 6S model for Hyperion data on May 7th 2005 and the analysis of spectrum for water data,this paper processes original spectrum data of 22 sample points using method of normalization and method of continuum removal.The regression models of chlorophyll content and general band ratio are established.Choosing the model with biggest correlation coefficient,the spacial distribution map of chlorophyll content in Nansi lake is acquired.The research results show: the method of continuum removal can remove background of water spectrum and enhance absorbability and reflection character of water spectrum and can increase the correlation coefficient of the models.Correlation coefficient of model using band ratio R700/R560 is biggest,which is 0.834.The model can satisfy the need of chlorophyll content estimation.