{"title":"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","authors":"S. Beygi, I. Talovina, M. Tadayon, A. B. Pour","doi":"10.1080/19479832.2020.1838628","DOIUrl":null,"url":null,"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.","PeriodicalId":46012,"journal":{"name":"International Journal of Image and Data Fusion","volume":"12 1","pages":"155 - 175"},"PeriodicalIF":1.8000,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/19479832.2020.1838628","citationCount":"21","resultStr":"{\"title\":\"Alteration and structural features mapping in Kacho-Mesqal zone, Central Iran using ASTER remote sensing data for porphyry copper exploration\",\"authors\":\"S. Beygi, I. Talovina, M. Tadayon, A. B. Pour\",\"doi\":\"10.1080/19479832.2020.1838628\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":46012,\"journal\":{\"name\":\"International Journal of Image and Data Fusion\",\"volume\":\"12 1\",\"pages\":\"155 - 175\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2020-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/19479832.2020.1838628\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Image and Data Fusion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/19479832.2020.1838628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Image and Data Fusion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19479832.2020.1838628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Alteration and structural features mapping in Kacho-Mesqal zone, Central Iran using ASTER remote sensing data for porphyry copper exploration
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.
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.).