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A comparative study for unmixing based Landsat ETM+ and ASTER image fusion

机译:基于混合的Landsat ETM +和ASTER图像融合的比较研究

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摘要

The mineral environment of the Bouaouane-Jebel (Hill) Hallouf mine, in the north of Tunisia, is monitored and analyzed by making use of the laboratory analysis and remote sensing images, ETM+ as well as ASTER VNIR and SWIR data, acquired in the same period. The main contribution of this paper consists of a methodology using multispectral multi-sensor fusion for the refinement of the mine tailing cartography around the studied mine. The developed methodology is based on the linear spectral unmixing approach which is applied to a multispectral hybrid image. This image was generated from the fusion of Landsat ETM+ and ASTER SWIR data. A comparative study is made between the hybrid and ASTER (VNIR and SWIR) images classification with respect to laboratory analysis. The given results show that the fusion of Landsat ETM+ and ASTER SWIR multispectral image yields the best mineral detection.
机译:通过使用实验室分析和遥感图像,ETM +以及同时采集的ASTER VNIR和SWIR数据,对突尼斯北部的Bouaouane-Jebel(Hill)Hallouf矿的矿物环境进行监测和分析。期。本文的主要贡献在于采用多光谱多传感器融合的方法来完善所研究矿山周围的矿山尾矿图。所开发的方法基于线性光谱分解方法,该方法应用于多光谱混合图像。该图像由Landsat ETM +和ASTER SWIR数据融合而成。在实验室分析方面,对混合图像和ASTER(VNIR和SWIR)图像分类进行了比较研究。给出的结果表明,Landsat ETM +和ASTER SWIR多光谱图像的融合产生了最佳的矿物检测。

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