高光谱遥感图像的地形校正和评价方法

发布时间：2018-03-21 10:05

本文选题：高光谱遥感　切入点：地形校正　出处：《山地学报》2016年05期 　论文类型：期刊论文

【摘要】：高光谱遥感具有光谱分辨率高,图谱合一的突出特点,在地质勘探和植被遥感等定量应用中,较全色和多光谱更有优势。然而目标区复杂的地形效应,是制约高光谱数据应用效果的诸多外界因素之一,利用地形校正模型消除地形影响,已成为目前高光谱遥感图像步入应用前的有效处理手段。目前的地形校正方法研究当中,遥感数据以多光谱居多,且校正效果的评价方法较之高光谱图像的特点也略显不足。通过朗伯体和非朗伯体假设的不同校正模型(C,SCS+C,Minnaert,Minnaert+SCS)对Hyperion遥感图像进行地形校正,并利用目视效果,分类标准差,目标反射率对比对校正结果分析评价,证明Minnaert+SCS模型最优,且评价方法合理,有效。
[Abstract]:Hyperspectral remote sensing has the outstanding characteristics of high spectral resolution and integration of maps. It has more advantages than panchromatic and multi-spectral applications in quantitative applications such as geological exploration and vegetation remote sensing. It is one of the external factors that restrict the application effect of hyperspectral data. Using topographic correction model to eliminate topographic influence has become an effective means of processing hyperspectral remote sensing image before its application. The remote sensing data are mostly multispectral, and the evaluation method of correction effect is also slightly less than that of hyperspectral image. The terrain correction of Hyperion remote sensing image is carried out by using different correction models of Lambert body and non-Lambert body hypothesis. The correction results are analyzed and evaluated by visual effect, classification standard deviation and target reflectivity comparison. It is proved that the Minnaert SCS model is optimal, and the evaluation method is reasonable and effective.
【作者单位】： 61206部队;61139部队;96633部队;
【分类号】：TP751

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