Utilization of ASTER data in lithological and lineament mapping of the southern flank of the Central High Atlas in Morocco

IF 0.9 Q3 GEOLOGY
Maryam Errami, A. Algouti, Abdellah Algouti, A. Farah, Saloua Agli
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引用次数: 0

Abstract

Abstract Geological mapping undoubtedly plays an important role in several studies and remote sensing data are of great significance in geological mapping, particularly in poorly mapped areas situated in inaccessible regions. In the present study, Principal Component Analysis (PCA), Band Rationing (BR) and Minimum Noise Fraction (MNF) algorithms are applied to map lithological units and extract lineaments in the Amezri-Amassine area, by using multispectral ASTER image and global digital elevation model (GDEM) data for the first time. Following preprocessing of ASTER images, advanced image algorithms such as PCA, BR and MNF analyses are applied to the 9ASTER bands. Validation of the resultant maps has relied on matching lithological boundaries and faults in the study area and on the basis of pre-existing geological maps. In addition to the PCA image, a new band-ratio image, 4/6–5/8–4/5, as adopted in the present work, provides high accuracy in discriminating lithological units. The MNF transformation reveals improvement over previous enhancement techniques, in detailing most rock units in the area. Hence, results derived from the enhancement techniques show a good correlation with the existing litho-structural map of the study area. In addition, the present results have allowed to update this map by identifying new lithological units and structural lineaments. Consequently, the methodology followed here has provided satisfactory results and has demonstrated the high potential of multispectral ASTER data for improving lithological discrimination and lineament extraction.
ASTER数据在摩洛哥中央高地图集南翼岩性和地貌制图中的应用
地质填图无疑在多项研究中占有重要的地位,遥感数据在地质填图中具有重要的意义,特别是在难以到达的地区。本文首次利用ASTER多光谱影像和全球数字高程模型(GDEM)数据,将主成分分析(PCA)、频带定量(Band Rationing)和最小噪声分数(Minimum Noise Fraction, MNF)算法应用于阿梅兹里-阿马辛地区的岩性单元映射和地貌提取。在对ASTER图像进行预处理后,将PCA、BR和MNF分析等先进的图像算法应用于9ASTER波段。结果图的验证依赖于研究区岩性边界和断层的匹配以及已有地质图的基础。除了PCA图像外,本文还采用了4/6-5/8-4/5的带比图像,对岩性单元的识别精度较高。MNF转换显示了比以前的增强技术的改进,详细说明了该地区的大多数岩石单元。因此,增强技术得到的结果与研究区现有的岩石构造图具有良好的相关性。此外,目前的结果允许通过识别新的岩性单元和构造线来更新这张地图。因此,本文采用的方法提供了令人满意的结果,并证明了多光谱ASTER数据在改进岩性识别和纹理提取方面的巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Geologos
Geologos GEOLOGY-
CiteScore
1.70
自引率
0.00%
发文量
7
审稿时长
12 weeks
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