Alteration and structural features mapping in Kacho-Mesqal zone, Central Iran using ASTER remote sensing data for porphyry copper exploration

IF 1.8 Q3 REMOTE SENSING

International Journal of Image and Data Fusion Pub Date : 2020-10-26 DOI:10.1080/19479832.2020.1838628

S. Beygi, I. Talovina, M. Tadayon, A. B. Pour

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引用次数: 21

Abstract

ABSTRACT Advanced Spaceborne Thermal Emission and Reﬂection Radiometer (ASTER) satellite imagery was used to identify argillic, phyllic and propylitic alteration zones and mapping geological structural features for porphyry copper exploration in the Kacho-Mesqal zone, Urumieh- Dokhtar Magmatic Arc, Iran. The image processing techniques such as specialised band ratio, Selective Principal Component Analysis (SPCA), and Spectral Angle Mapping (SAM) image processing methods were implemented to the visible and near-infrared and shortwave infrared bands of ASTER. Results indicate that the argillic alteration zone is broadly distributed in the granodiorite intrusion, andesitic rock, tuff breccia and ignimbrite. Phyllic alteration is mainly mapped associated with sandstone and some parts of andesitic lithology. Propylitic alteration zone is identified in andesite, sandstone, shale and marl, dacite to rhyodacite, andesite-basalt, tuff and andesite lava and granodiorite intrusion. The fracture density map shows that the argillic alteration is mostly abundant in the high-density fracture zone, whereas propylitic and phyllic zones are located in moderate to low-density fracture zones. Consequently, high potential zones for copper mineralisation in the study area are identified within the high to moderate fracture density zones associated with argillic and assemblage of argillic, phyllic and propylitic alteration zones in granodiorite and andesite units.

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利用ASTER遥感数据进行伊朗中部kcho - mesqal地区斑岩铜矿蚀变及构造特征制图

摘要：高级星载热发射和反射辐射仪（ASTER）卫星图像用于识别泥质、千枚岩和丙基蚀变带，并绘制伊朗乌鲁米耶-多赫塔尔岩浆弧Kacho-Mesqal带斑岩铜勘探的地质结构特征。对ASTER的可见光、近红外和短波红外波段，采用了专门的波段比、选择性主成分分析（SPCA）和光谱角映射（SAM）图像处理方法等图像处理技术。结果表明，泥质蚀变带广泛分布于花岗闪长岩、安山岩、凝灰岩角砾岩和熔结凝灰岩中。Phyllic蚀变主要与砂岩和部分安山岩岩性有关。在安山岩、砂岩、页岩和泥灰岩、英安岩至流纹岩、安山岩玄武岩、凝灰岩和安山岩熔岩以及花岗闪长岩侵入体中发现了丙基蚀变带。裂缝密度图显示，泥质蚀变主要集中在高密度裂缝带，而叶绿质和千枚岩带位于中等至低密度裂缝带。因此，研究区域内的铜矿化高潜力区位于与花岗闪长岩和安山岩单元中的泥质和泥质、千枚状和丙基蚀变带组合相关的高至中等断裂密度区内。

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来源期刊

International Journal of Image and Data Fusion REMOTE SENSING-

CiteScore

5.00

自引率

0.00%

发文量

期刊介绍： International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making. Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management. The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).