高光谱遥感技术在植被信息提取中的应用

Application of Hyperspectral Remote Sensing Technology in Vegetation Information Extraction

高光谱遥感技术与传统遥感技术相比,有着图谱合一和光谱连续的优势,能够实现地物的准确识别和精细分类,并且在岩矿信息提取方面取得了显著成果,然而在植被信息提取中的研究尚处于发展阶段。随着农作物估产和土地利用监测等领域对植被精细信息的要求日益提高,高光谱遥感在植被研究中的应用显得越发重要。本文针对高光谱在植被信息提取中的应用进行研究,实现传统多光谱遥感难以完成的准确识别与分类。

Hyperspectral remote sensing technology has been successfully used in distinguishing and classifying tiny objects due to its higher spectral resolution. It has broken the restriction of traditional multispectral remote sensing, which has difficulty in realizing various spectrum on the surface of the ground. So far, there are many researchers have studied the application of hyperspectral remote sensing technology in geological sciences and achieved gratifying successes. However, it is only at the first step of study in vegetation information extraction. With the development of several fields, such as environmental monitoring and estimating, agriculture, detection of renewable and un-renewable resources and the like, application of hyperspectral in the study of vegetation will become increasingly important. For keeping abreast of current development in science and technology, this thesis tentatively studies the application of Hyperspectral remote sensing in vegetation information extraction.