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The Zafarghand area is located as a porphyry Cu deposit in the northeast of Isfahan and the southeast of Ardestan, which is a part of the Iran-Central structural zone; More precisely, it is located in the Urmia-Dokhtar volcanic belt. In the porphyry Cu deposits exploration, identifying and determining the alteration zones is of special importance. The aim of the present study is to identify and highlight the alteration zones of Zafarghand area, with the help of fractal geometry in the processing of ASTER sensor satellite images. Accordingly, considering the raster nature and digital form of satellite images, the digital number values of each pixel from the image matrices were considered as samples in a systematic network. Finally, the algorithm of the Concentration-Area (C-A) fractal model was implemented as an efficient method for determining anomaly samples in the set of digital number (DN) values of ASTER satellite image pixels. The alteration zones identified with the help of the aforementioned technique based on their expansion in the region represent the very effective performance of this method. So that, especially in the case of phyllic and propylitic alterations, there is a very high correspondence between the results of satellite image processing and the spread of alterations in field studies. The non-identification of potassic and argillic alterations in the obtained results is also directly related to their limited expansion in the study area. Finally, it could be acknowledged that the application of the fractal C-A method (considering its structural nature) in decision-making has been successful and has proven to be very effective in determining the alteration zones in the Zafarghand area.

This study aims to use the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data to identify promising areas and design a targeted preliminary survey in the Karijgan area located in Khosuf-Birjand. Therefore, at first, necessary pre-processing, such as atmospheric and topographic corrections, was applied to the data. Then, from conventional processing methods on multispectral data, including band ratio, principal component analysis (PCA), and its improved type, the selective principal component analysis method (CROSTA), promising areas were identified. In this case, by using the band ratio method, index areas prone to iron oxides, silica, carbonate, chlorite and epidote, alunite, kaolinite and pyrophyllite, sericite, muscovite, illite, and smectite were identified. Also, with the Crosta method, various types of main alterations (propylitic, argillic, and phyllic) were determined. Finally, by combining the results, promising areas were identified for preliminary surveys. A check field and sampling of the identified areas were done to validate the processing results. The results of the sample analysis by ICP-OES and X-ray diffraction (XRD) showed good agreement and accuracy with the results obtained from the remote sensing processing of the Karijgan area.

Separation and mapping of alteration zones is of special importance in the exploration of porphyry copper types. In order to highlight these alteration zones, remote sensing techniques have been applied. Zafarghand region is located in the southeast of Ardestan and northeast of Isfahan. Based on the division of geological structural zones, it is located in the Central Iran zone and also in the middle part of Urmia-Dokhtar magmatic volcanic arc. In this area, there are different alteration halos, including phyllic, potassic, propylitic, argillic, and slightly siliceous. In this study, argillic, phyllic, propylitic, and clay alterations have been identified using ASTER sensor images. Moreover, LANDSAT 8 images have been employed to identify clay and iron oxide alterations. In this regard, after performing the necessary pre-processing, methods of False Color Combination (FCC), Band Ratio (BR), Least Squares-Fit (LS-Fit), Matched Filtering (MF), and Principal Combination Analysis (PCA) were applied to reveal the zones containing these alterations. Among the applied methods, the LS-Fit and MF in Aster images, as well as the BR method in both images, and the PCA method in Landsat 8 have brought good results.

The world-class Neyshabur turquoise mine is hosted by a Tertiary volcano-sedimentary sequence that belongs to the Binaloud zone, in northeastern Iran. Binaloud Mountain has experienced a complicated geological history and several tectono-magmatic periods as a result of its especial tectonic setting. Continuing compression in Late Alpine orogeny deformed the magmatic rocks and brought extensive alteration in this belt. Based on field-experimental studies, the lithological units of the turquoise mine area of Neyshabur can be divided into three sections: volcanic rocks, subvolcanic rocks, and different types of breccia. Andesite, trachyandesite, trachyte lavas, and pyroclastic rock units of the Eocene are among the most important in the study area. These rocks have undergone intense alteration due to the intruded of subvolcanic intrusive bodies. The extent and intensity of the alteration are significant in volcanic and intrusive rocks of this region. The main objectives of this study are to detect and mapping of hydrothermal alteration zones using ASTER data and field studies for future explorations of turquoise mineralization.

 Introduction :

Hydrothermal alteration zones have a significant role in the prospecting of mineral deposits. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) contains appropriate spectral and spatial resolution to detect spectral absorption features of hydrothermal alteration minerals. The highly brecciated and altered part of andesite, trachyandesite, and trachyte units is the main host of high quantity and quality veins, veinlets, and concretion of turquoise in the study area. Therefore, mapping and identification of hydrothermal alteration mineral assemblages using ASTER satellite remote sensing data can be considered as a cost-effective and applicable tool for targeting and prospecting this mineralization.  

Methodology and Approaches :

  Image processing techniques were applied on the digital subset ASTER data covered the turquoise mine area of Neyshabur. Recognition of hydrothermally altered rocks was carried out using color composite images (RGB), ratio images (BR), relative absorption band depth (RBD), matched filtering (MF), and spectral angle mapper (SAM). The results obtained in this section were controlled by field studies.

 Results and Conclusions :

The mentioned image processing techniques and field studies have been successfully used in the mapping of hydrothermal alteration zones in the study area. According to the outcome of ASTER image processing and field studies, hydrothermal alterations zones could be classified into five groups: silicic-gossan, serisitic, propylitic, advanced argillic, and argillic zones that silicic-gossan and advanced argillic zones forming the most and least extent in alterations zone respectively. The MF algorithm shows very clearly the gossan altered zones in the study area. Moreover, the results indicate that the SAM method is promising for identifying serisitic, propylitic, advanced argillic, and argillic zones and can assist exploration geologists to find new prospects of turquoise mineralization in the other regions before costly detailed ground investigations. The results obtained from image processing are also consistent with the results of field studies petrographic.

Exploration of the new mineral deposits around the existing mines is an important objective in mining industry. Using multispectral remote sensing images, due to their diversity and vast availability is a useful tool to meet this purpose. In this research, the Zonouz region was investigated for discovering new high potential kaolinite mineralization areas using Landsat8 and ASTER data. Zonouz kaolin mine which is located in Marand county, East-Azarbaijan, is the biggest kaolin deposit in the Middle-East. In the current research, the capability of Landsat8, as a new generation multispectral data, and ASTER data were examined in mineral detection. At first, the preprocessing of data, i.e. atmospheric and topographic corrections and elimination of the vegetation cover were carried out. Then, the spectral profiles of the endmembers of the study area datasets were extracted. Identification of the extracted endmembers was done by comparison of the unknown spectra with reference spectra of the USGS spectral library, and 3 minerals including kaolinite, quartz, and Fe-bearing minerals were identified. Finally, the distribution maps of the identified minerals were extracted by using of the artificial neural networks, as a non-linear supervised method. To the best of our knowledge, the applied neural networks structure has not been implemented on LANDSAT 8 and ASTER data earlier. This research is also the first implementation of LANDSAT 8 and ASTER data in Zonouz kaolin region for extension mapping of the kaolin. Two different approaches including virtual verification and field sampling were applied for validation of the results. According to the Findings of this research, both of ASTER and Landsat8 datasets proved successfulness for identifying the kaolinite; but the Landsat 8 data exhibited better performance in detecting and mapping of the quartz and hematite. Finally, 6 promising areas were determined as high potential zones of kaolinite mineralization for future studies.

In this study, processing and interpretation methods in remote sensing such as visual and spectral analysis have been performed on the ASTER (advanced spaceborne thermal emission and reflection radiometer) data from northeast of neyriz area, and as a result, the alteration zones in the area have been identified. Then, the results of magnetometric data, using geological information, alteration and mineralization from the have been interpreted. The emergence and expansion of a measuring instrument for geological and mineralogy in the field of mine mineral resources in recent decades are due to the importance of this industry. The study area is located in the northeast of neyriz and near the village of Ghori in Fars province. Geologically, the units of the study area are located in the zone-Sanandaj-Sirjan and with the general northwest-southeastern trend.

In this study, satellite images, and aeromagnetic data were analyzed to investigate the geothermal potential in the Ardebil-Sabalan area in Ardebil province. Thermal activity monitoring in and around active volcanic areas using remote sensing is an essential part of volcanology nowadays.In this study, a geothermal survey is conducted in sabalan area of Ardebil province in NW IRAN using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and ASTER (AST L1B) sensor. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. The magnetic investigations showed that a deep magnetic anomaly exists in the southern part of the area. These magnetic anomalies were correlated with thermal anomalies. 

Development of advanced tools in remote sensing and geophysical exploration geothermal during recent decades indicates the necessity and importance of these tools in industry. They defined thermal anomalies as areas with temperatures higher than the spatial background. Thermal infrared (TIR) remote sensing is one of the essential methods to prospect the geothermal resources. Remote sensing is an important technique for activity monitoring in and around active volcanic areas in this study, a geothermal survey is conducted in the Sabalan area of Ardebil province in NW IRAN using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and ASTER sensor and Geophysical Aeromagnetic data analyzing. Thermal infrared remote (TIR) sensing is an efficient technique to obtain the land surface temperature (LST). With ever increasing attempts on looking for alternative energy sources, TIR remote sensing has become a popular technique in the exploration of geothermal resources. The first application of TIR remote sensing in geothermal exploration can be dated back to the middle of 20th century. The aim of this study is to analyze remote sensing and Aeromagnetic data for evaluating the geothermal potential zones in an area located in the eastern of Ardebil Province. 

The data studied in this research includes ASTER – ASTL1 B (day and night) reflectance and LST products, for the year 2009, Landsat ETM+ day-time image on 2015, aeromagnetic data collected by Houston Texas Co., America, in 1974-1977. A comparison of the day-time and night-time images can reveal the surface thermal differences for detecting geothermal anomalies. In order to identify geothermal zones, image processing land surface temperature (LST) methods using ENVI software were applied on the using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and ASTER sensor and Geophysical Aeromagnetic data analyzing from the study area. 

The results of this work also suggest that TIR remote sensing is an important technique for geothermal exploration with its high efficiency, simplicity and accuracy in temperature retrieval. Three thermal anomalies were detected on the maps and charts obtained for the average temperature difference and apparent thermal inertia. One anomaly is located in the Sabalan area and the other one is situated in the Northern part of the Ardebil side. the results of magnetic interpretations confirmed thermal anomalies showing a deep magnetic anomaly in the southern region and another magnetic anomaly in the hot spring.

Summary: Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data and Interactive Data Language (IDL) logical operator algorithms with calculating threshold based on the land, and experimental laboratory analysis, were used to map hydrothermally altered rocks in the Sar Cheshmeh, Darrehzar, Nowchoon, Seridune and Sarkuh areas. Hydrothermal alteration enhanced by this method include silicic (hydrous quartz, chalcedony, opal), propylitic (calcite and epidote- chlorite), argillic (alunite-pyrophyllite-kaolinite) and phyllic (sericite-illite). By use of this method, different types of hydrothermal alteration in and around mineral deposits such as Sar Cheshmeh and Darrehzar, based on field observations and sampling, confirmed. Calcite and epidote- chlorite minerals were separated in the propylitic zone based on the logical operator algorithms.
Band ratios are based on the absorption and reflection parts of the electromagnetic spectra of minerals. In order to minimize the interferences from other sources such as vegetation cover, combined use of band ratios are suggested by different workers. Logical operators suggested by Mars and Rowan (2006) and Mars (2013) are used here for mapping different minerals associated with hydrothermal alterations. The important point in using these logical operators is the proper selections of the threshold for each alteration type. This point is discussed in this paper.
Methodology and Approaches: ASTER data used for hydrothermal alteration mapping using the combined band ratio method. The combination of different band ratios with specified thresholds, is used to map hydrothermally altered areas. The threshold values are calculated based on both statistical method and field/laboratory observations. Finally, logical operators suggested by Mars and Rowan (2006) and Mars (2013) used for this purpose. The result will be a binary image based on true (presence of alteration, which is one) or false (absence of alteration, which is zero) for each pixel of the image. The alteration maps obtained are evaluated using field and laboratory observations.
Results and By use of this method, different types of hydrothermal alteration in and around mineral deposits such as Sar Cheshmeh and Darrehzar, based on field sampling/laboratory observations, confirmed. In areas such as Seridune due to the weathering of host rocks, phyllic and argillic alterations are observed together. Calcite and epidote- chlorite minerals were separated in the propylitic zone based on the logical operator algorithms. Sampling results and field observations have confirmed the alteration maps.