利用大地遥感卫星 8 号对贝努埃海槽上游部分地区进行岩性判别和绘图

O.A. Abodunrin, B.J. Fagbohun, A.Y.B. Anifowose
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引用次数: 0

摘要

这项研究的重点是评估利用大地遥感卫星 8 号数据对贝努埃海槽上部进行岩性判别和绘图的图像增强技术的效率和互补性。为此,在覆盖贝努埃海槽上部部分地区的 Landsat 8 OLI 数据上应用了最佳指数因子、波段比、主成分分析和最小噪声分数等图像增强技术。利用这些图像增强技术的三个信息量最大的衍生物创建了假彩色合成(FCC)。通过将 FCC 与现有地质图进行比较,对 FCC 区分研究区域不同岩性单元的能力进行了比较。结果显示,根据波段比率创建的 FCC 提供的信息量最大,而根据最佳指数因子创建的 FCC 在岩性区分方面提供的信息量最小。此外,根据带比、主成分分析和最小噪声分数的导数创建的 FCC 具有互补性。因此,将这三种增强方法产生的三个 FCC 融合为一幅图像,可进一步帮助进行岩性判别。通过综合三种图像增强技术的输出结果,研究区域内的大部分沉积岩和结晶岩都被成功地划分出来。本研究采用的方法,特别是将波段比、主成分分析和最小噪声分数的输出结果融合在一起的方法,是一种新颖的方法,适用于偏远地区的岩性绘图,特别是有大量岩石裸露的干旱和半干旱地形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lithological discrimination and mapping in part of the upper Benue Trough using Landsat 8
This study focused on evaluating the efficiency and complementarity of image enhancement techniques for lithological discrimination  and mapping in the upper parts of Benue Trough using Landsat 8 data. To achieve this, image enhancement techniques such optimum  index factor, band ratio, principal component analysis, and minimum noise fraction were applied on Landsat 8 OLI data covering parts of  the Upper Benue Trough. False colour composites (FCC) were created from three most informative derivatives of these image  enhancements. The FCCs were compared in terms of their capability to differentiate different lithological units in the study area by  comparing the FCCs with existing geological map. The results show that the FCC created from band ratios provided the highest amount  of information, while those created based on optimum index factor provided the least amount of information with respect to lithological  discrimination. Additionally, it was observed that the FCCs created from the derivatives of band ratio, principal component analysis and  minimum noise fraction provide complementarity. Thus, the three FCCs from these three enhancement methods were fused into a single image, which further aided lithological discrimination. By combining the outputs from three image enhancement techniques, most of the  sedimentary and crystalline rocks in the study area were successfully delineated. The method adopted in this study particularly the fusion  of outputs from band ratio, principal component analysis and minimum noise fraction represents a novel approach that is suitable  for lithological mapping in remote areas, particularly arid and semi-arid terrains with considerable rock exposure.  
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