【摘要】 融合数据因其综合了不同遥感数据源的优势,充分协同利用了多源信息,被广泛应用于各个领域。SPOT-5遥感卫星集合了多重分辨率、多种遥感器于一身,该特点使得它在资源环境调查和规划与动态监测、地图制图与更新等领域得到广泛应用。本文从SPOT-5数据的自身融合和SPOT-5与ETM+数据融合两方面着手,利用遥感应用中常用的HIS变换、Brovey变换、HPF变换,探寻有利于植被识别的融合方法。结果表明:1)HPF变换对目视判读最为有利,依次是Brovey变换法、HIS变换法;2)SPOT-5数据自身融合的视觉效果优于SPOT-5与ETM+两种数据融合的;3)将植被分为5种类型,对SPOT-5自身融合影像进行目视判读,再通过实地验证,得出HPF变换、Brovey变换、HIS变换的加权精度分别为:82.99%、79.01%、71.02%。更多还原

【Abstract】 Because data fusion could take the advantage of multisource remote sensing data and could make the best use of information,it’s used in many domains.The SPOT-5 satellite has multi-resolution and multi-sensor together,which makes it widely used in the investigation and programming of resources and environment,dynamic inspection,cartography and its update.This paper begins with the fusion of SPOT-5 data and SPOT-5 PAN band with ETM+ multi-spectrum bands,using the methods of HIS transformation,Brovey transformation and HPF transformation to find which one is useful for vegetation identification.The result shows that: 1)among the three methods HPF transformation is the best one,followed is Brovey transformation and HIS transformation;2)in the case of visual comparison,the fusion images of SPOT-5 itself is better than those fused of SPOT-5 and ETM+.In this study,the vegetation was divided into 5 categories.After interpreting the fusion images of SPOT-5 itself and field validating,we find that the weighed accuracy of HPF transformation,Brovey transformation and HIS transformation is 82.99%,79.01% and 71.02%.更多还原