基于ETM+影像的山区植被信息提取研究
首发时间:2012-11-26
摘要:植被在遥感影像上成像的复杂性和不确定性,使得利用遥感技术提取植被信息具有很大的难度,而植被信息又往往是遥感影像中重要的一种要素。本文使用数据资源丰富的ETM+数据对新疆西天山地区的植被进行提取研究,目的是为进一步的矿化蚀变信息提取做准备。为保证较好的保留矿化蚀变信息,在认真分析了植被和矿化蚀变的光谱特征的基础上,提出采用"面向特征的主分量分析+最优密度分割法",最后得出采用ETM+波段3和波段4组合的方式能够较好的提取出植被信息,该方法具有一定的使用价值。
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Study on the Extraction of Vegetation in Mountain Area Based on the ETM+ Image
Abstract:Vegetation has such a complexity and uncertainty in remote sensing image that the extraction of vegetation by using remote sensing is very difficult work,but it is often an important element in image. In this paper vegetation is extracted using ETM+ data in area of west Tianshan,Xinjiang in order to subsequently extract the minerals alteration. In order to ensure better keep minerals alteration,the paper proposes the feature-oriented principal component analysis + optimal density segmentation based on the careful analysis of spectral feature of vegetation and minerals alteration. The results show that using ETM+ band 3 and band 4 combinations can better extract vegetation and this method has certain value in use.
Keywords: remote sensing vegetation ETM+ Principal Component Analysis(PCA)
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