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ERS-2 SAR and IRS-1C LISS Ⅲ data fusion: A PCA approach to improve remote sensing based geological interpretation

机译:ERS-2 SAR和IRS-1C LISSⅢ数据融合:一种PCA方法,可改善基于遥感的地质解释

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摘要

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS Ⅲ image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.
机译:在本研究中,已经尝试将光学孔径雷达和合成孔径雷达数据融合,以绘制Singhbhum剪切带(SSZ)及其周围区域的各种岩性单元。研究区域的ERS-2 SAR数据已使用基于快速傅立叶变换(FFT)的滤波方法以及弗罗斯特滤波技术进行了增强。然后,使用主成分分析(PCA)技术将这两种增强的SAR图像分别与直方图均等化的IRS-1C LISSⅢ图像融合。后来,面向特征的主成分选择(FPCS)技术已应用于生成伪彩色合成(FCC)图像,从中准备了相应的地质图。最终,GIS技术已成功地用于已发布的地质图和基于融合的地质图之间的岩性解释中的变化检测分析。通常,在大部分研究区域中,这些地图之间具有良好的一致性。基于变化检测研究,几乎没有地方需要识别,需要进一步进行详细的地面地质研究。

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