AVIRIS高光谱遥感数据的植被信息提取

Vegetation Information Extraction Based on AVIRIS Hyperspectral Remote Sensing Data

以Moffett Field的AVIRIS高光谱遥感影像为对象,应用基于信息量的自适应波段选择方法实现植被信息提取的最优波段组合,在此基础上采用监督分类为主、目视解译为辅的信息提取方法,在ENVI和ERDAS遥感图像处理软件中进行分析与处理,实现植被信息提取。结果表明,与多光谱遥感数据相比,高光谱遥感数据具有更强的植被信息识别能力,提取的植被信息更丰富。

The vegetation information of Moffett Field was extracted based on the AVIRIS hyperspectral remote sensing data.First of all,the optimal band combination of hyperspectral remote sensing image for vegetation information extraction was obtained through adaptive band selection based on the information quantity.Secondly,the vegetation information was extracted mainly through supervised classification with the assistance of visual interpretation by remote sensing image processing software ENVI and ERDAS.The result showed that the vegetation information recognition ability of hyperspectral remote sensing data was stronger than that of multi-spectral remote sensing data,and the vegetation information obtained was more informative.