利用遥感、地理信息系统、实地研究和实验室数据对埃及中东部沙漠Wadi Hammamat地区进行地质制图

Moamen M. Badr, Ahmed M. El Mezayen, S. M. Salem, Sherif A. Taalab
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引用次数: 0

摘要

在本研究中,使用了操作陆地成像仪(OLI)图像和几种处理方法来描绘Wadi Hammamat地区的不同岩石单元。为了验证遥感数据,利用地理信息系统(GIS)和实地研究制作了Wadi Hammamat地区1:20 000比例的地质图。利用假彩色合成(FCC)、主成分分析(PCA)、最小噪声分数(MNF)和频带比(BR)等多种图像处理方法对研究区地质图进行了改进和修正。FCC 761762和751 RGB的最佳波段组合。PCA结果显示,PCA1、PCA2、PCA3岩性分异良好,PC5、PC2、PC3岩性分异效果最好。其中,它可以区分不同类型的Hammamat糖蜜沉积物;哈玛玛特格雷瓦克,哈玛玛特粉砂岩和哈玛玛特砾岩。提出了一种新的FCC带比(7/5,5/3&3/1)作为最佳岩性判别方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geological mapping using remote sensing, GIS, field studies and laboratory data of Wadi Hammamat area, Central Eastern Desert, Egypt
In the present study, the Operational Land Imager (OLI) images have been used with several processing approaches for delineating the different rock units of the Wadi Hammamat area. To validate the remote sensing data, a geological map of the Wadi Hammamat area at a scale of 1:20,000 was produced using a Geographic Information System (GIS) and field research. The geological map of the research area has been improved and modified using several a variety of image processing methods, such as False color composite (FCC), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Band Ratio (BR). The best band combination of FCC 761,762 and 751 RGB. The result of PCA is PCA1, PCA2 and PCA3 show well lithological differentiation, while the best result of PCA is PC5, PC2, and PC3. In which it can distinguish between the different types of Hammamat molasse sediments; Hammamat graywacke, Hammamat siltstone, and Hammamat conglomerate. A new proposed FCC band ratio (7/5,5/3&3/1) has been developed as a best lithological discrimination.
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