جستجوی مقالات مرتبط با کلیدواژه « aster » در نشریات گروه « زمین شناسی »

The Sonajil porphyry Cu deposit is 15 km east of Harris City in East Azerbaijan province. Mineralization has often been reported as hydrothermal of various origins and structural geological control of Cu metal in the region. Geochemical exploration is beneficial and cost-effective for surveying metal deposits on a regional scale. To achieve this, the concentration-number fractal geometric method is used, which takes into account the spatial position and the pattern of geochemical data distribution. In geochemical communities resulting from the decomposition of copper metal in 1224 samples of sediments, the minimum and maximum grade for Cu metal is 160 ppm and 5600 ppm, respectively. In the next step, using remote sensing studies and processing of ASTER satellite images, the hydrothermal alterations of the region were identified. For this purpose, the range of visible to infrared waves of short wave (VNIR-SWIR) of ASTER images has been used to identify argillic, and propylitic alterations. The results showed that argillic alteration was more extensive than other alterations in the region and significantly affected the formation of the Sonajil Cu deposit. In general, the results of these methods showed that the concentration of Cu metal increases in the south and southwest and in these areas the concentration of Cu metal is very high; The severity of geochemical anomalies has increased near geological structures such as faults and shear zones. Field control indicates a high probability of mineral reserves in the target areas.

Today, remote sensing in geology efficiently identifies alteration zones and suitable locations for hydrothermal deposits. In the present study, satellite image processing techniques are employed to highlight the alteration zones in the Zafarghand exploration area. Zafarghand, located in the northeast of Isfahan, falls within the Central Iran zone according to geological structural zoning (the middle part of the Urumieh-Dokhtar magmatic arc). The Zafarghand porphyry system includes phyllic, potassic, propylitic, argillic, and silicic alteration halos. In this study, ASTER sensor images are used to identify the associated alterations. Due to the raster and digital nature of satellite images, the digital number (DN) values of each pixel in the image matrix are considered as samples in a systematic grid. Ultimately, the singularity method algorithm, as a structural approach for effectively separating geochemical anomalies, is applied to the DN values of ASTER satellite images. Additionally, the fuzzy gamma operator was used to integrate available information layers from the study area, including the lithological layer, fault density, false color composite with ASTER bands 468 (RGB) based on new DN values (calculated α values), and the Cu geochemistry layer. The results from this technique demonstrate that the singularity method, due to its structural nature, is successful in decision-making and effectively identifies alteration zones in the Zafarghand area, particularly propylitic and phyllic alterations. Furthermore, it was observed that the fuzzy gamma operator, using the proposed technique in this study, successfully highlights prospective Cu mineralization areas in the Zafarghand exploration area.

The studied area is located in Zaviyeh 1:100000 sheet and included parts of Tehran, Qom, and Markazi provinces. There are geological units related to the Mesozoic and Cenozoic eras in this area, the volcanic igneous rocks of the Eocene and younger volcanic rocks are alternating of acidic rocks with a composition of dacite to rhyolite and medium to basic rocks of andesite to andesite-basalt. In the Zavieh area, the existing igneous rocks are part of the magmatic belt of Urmia Dokhtar, which is a suitable host for porphyry copper deposits. Since alteration are a good exploratory guide for the identification of porphyries, in this study using aster and sentinel sensor images, various hydrothermal alterations in the region (such as argillic, propolytic, silicic, carbonate and iron oxide alterations) have been investigated by band ratio and colour composite analysis. The processing results of the images obtained from the aster and sentinel sensors are highly reliable for detection of different types of clay minerals and iron oxides, respectively. On the other hand, today, geographic information system (GIS) and fuzzy logic in data integration and modeling have found a very important role in the exploration and estimation of mineral reserves to introduce promising mineral areas. In this research, after the integration of remote sensing and geological information, using fuzzy logic and Index overlay method; prone areas to mineralization were identified. Based on field observations, copper mineralization was observed in the form of malachite stains in some prosperous area.

Fractal modeling is a useful tool for classifying various natural phenomena. Fractal methods evaluate relationships between all parameters, such as geochemical data and spatial distribution, without any data normalization. For this reason, fractal models are more exact and closer to reality. In this study, 1292 samples of Stream sediments on the 1:100000 geological sheet of Varcheh in the south of Arak were surveyed for geochemical exploration and analyzed by the ICP-MS method to detect 15 elements. The statistical parameters of Zn, Pb, Cu, and Ba, and histograms for these 15 elements showed a right-skewed distribution. In this case, the fractal method is among the best techniques for separating anomalies from the background. The element data were analyzed by the concentration-number (C-N) fractal method and then matched to alteration zones and faults plotted by ASTER multispectral imagery to detect minerals. The C-N fractal diagram was plotted for Zn, Pb, Cu, and Ba, and the most intensive anomalies for these elements have a grade greater than 524.8, 794.3, 223.9, and 944.1, respectively. Integrating the anomaly maps for Zn, Pb, Cu, and Ba with iron oxide, proplytic, argillic, and silicic alterations, fault maps, and the maps of mines and Varcheh mineral indices showed that the metal mines have mainly occurred in regions with a high fault density. The separated Pb and Zn anomalies are consistent and related to high fault and fracture density regions. They are also highly correlated with the silicic alteration plotted in the region.

Qarah Gol area is located in Ahar-Arasbaran metallurgical zone in Ardabil Province, Meshkinshahr city in Moradloo section. The oldest rock units in the study area are related to the Cenozoic (Eocene), which consists of volcanic breccia. In this area, microquartzdiorite have penetrated into volcanic and pyroclastic rocks and alteration and mineralization have taken place on a weak scale. The results of Aster image processing, using absorption bands and selection of the best ratio color composite (5 + 7.6, 9.8, 4.5) respectively for the detection of argillic, phyllic and propylitic alterations, as well as using techniques such as principal component analysis and spectral angle mapping indicate that associated alterations in the central part of this deposit is consistent with petrographic studies in Qarah Gol area. Field studies have shown that the results of Spectral Angle Mapper (SAM) have performed better than the principal component analysis (PCA) in the detection of alterations.

The Mehdiabad zinc-lead deposit, which is located at the East of Mehriz city, is a carbonate-hosted ore deposit lying in the dolomitic rocks of Taft Formation. This deposit is composed of oxide-carbonate and sulfide ores. Different spectral processing techniques were applied to ASTER and Landsat 8-OLI multispectral images to detect different mineralization zones and associated alterations. In OLI image, Principal Component Analysis, Independent Component Analysis, and Band Combinations consisting of Band Ratios were successful for detecting mineralization zones and associated alterations. In ASTER image, the best results were obtained from Principal Component Analysis and Linear Spectral Unmixing methods. Based on the results of this study, zinc-lead mineralization occurred in the areas where gossan and siderite alteration zones overlap. The results of the spectral techniques were confirmed by field studies and X-Ray Diffraction analysis of the obtained samples.

The Tutak area (northeastern part of Shiraz city) located in Sanandaj-Sirjan metamorphic Zone (SSZ) was chosen as study area because of having two important resources of iron and copper. Two metamorphic complexes of SSZ namely Surian and Tutak are the main host of these resources. The algorithms of Spectral Information Divergence and Adaptive Coherence Estimator were used to detect and distinguish rock units and indicator minerals. Using spectra of field samples, the pixel-based algorithm of Spectral Information Divergence enhanced greenschist and marble lithological units because of their significant spectral differences in VNIR region. Overall accuracy and kappa coefficients resulted by using this algorithm for detection of rock units were 0.83 and 0.72, respectively. Using data of USGS spectral library, the outputs of the sub-pixel algorithm of Adaptive Coherence Estimator successfully identified pixels with high abundances of chlorite and ankerite. Results showed that chlorite areas with its abundances more than 50% overlapped greenschist units, and the areas with chlorite abundances above 75% had acceptable conformity with the copper deposits, most prominent of which is Mazaijan copper deposit. The areas with more than 50% ankerite overlapped the marble units, and its abundances above 75% indicated an increase of the abundances of this mineral compared to the minerals of calcite and dolomite in this rock unit with approaching iron mineralization. So, based on study results, the Adaptive Coherence Estimator technique can be suggested to accurately detect and distinguish the minerals of the mineralogical reservoirs in study area.

This area has been located in a scene ETM No. 164-37 and ASTER linear band prediction satellite image No. AST-L1A:002:ASTL1A 0108220733380109011021. Such measured images in different band combinations will be used for extracting of geological structures and types of alterations (iron oxide, Argillite and Carbonate) and for detecting different stones and minerals of the ground, a spectrum range of 1.5 to 2.5 μ is very important.This range includes short to average IR range covering six linear band predictions (SWTR bands). On the other side, to use spectral reflectance curves of such minerals in USGSENVI spectral library for spectral analysis, it is necessary to resample the curves to the spectral range of ASTER. Linear Band Prediction methods, LS-Fit, Matched Filtering and BandRATIO used of ASTER images for all Minerals and iron alterations and for iron oxides there were also used visual interpretations and ETM images were used in band combination of RGB:531. Considering the petrological and geological situation of studied area (Scale 1:25000 of Kamoo), the type of Alteration and its index minerals detailed as below; Alteration of iron (Gotit, Hematit and Jarosit and Limotit), alteration of Argilic (Kaolinite, Motmorilonit, Ilite and Haloysite) and carbonate (Calcite and Dolomite) have been considered. Alterations present in remote sensing studies are in conformity with field and results obtained fromtypes of analysis conducted.

The performance of various spectral processing techniques has been studied and evaluated using the ASTER and OLI satellite images of the Shahrak mining district. The district is located 60 kilometers north of Bijar city, Kurdistan province. Different band ratios and false color composites were prepared to determine which of them are more adequate for the detection of iron occurrences, chlorite-epidote and clay alteration. Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Minimum Noise Fraction (MNF) transforms were also applied to the bands of ASTER and OLI images. The extracted images indicate the OLI image in the PCA method is better than the ASTER image, and is able to detect iron mineralization and clay alteration more efficiently. In the ICA technique, the OLI image also reveals more details, so that the color combination IC3, IC2, IC1, in addition to identifying the above phenomena, also has a high potential for lithological mapping. In the MNF transform, the OLI image performs better than the Aster image. From the three transforms applied, ICA and then MNF had better outcomes than the PCA in the OLI image.

Mineral exploration in Esfandagheh area, located in south east of Kerman province is complicated due to verity of metallic deposits including volcanogenic massive sulfide copper, skarn iron, and volcanic manganese. This research was carried out with the aim of defining a model for mineral exploration and providing mineral potential map using remote sensing data. ASTER and OLI images along with various image processing techniques including color composite of band ratios, principal component analysis (PCA), and QI and SI indices were applied to recognize the hydrothermal alteration halos. Result validation was done through field and laboratory studies. Argillic, phyllic, propylitic, and iron oxides/hydroxides alterations were enhanced using color composite ratios of ASTER bands like (B4+B7)/B6 in red, (B4+B6)/B5 in green, and (B7+B9)/B8 in blue. Hydrothermal alteration mapping was also accomplished using selected PCA of OLI 2, 4, 6, and 7 bands, ASTER 4 to 9 bands and a combination of OLI 2 and 4 bands along with ASTER 4 to 9 bands. ASTER thermal infrared bands applied to determine QI and SI indices for enhancing silicic halos. Mineral potential map was produced through integrating alteration maps by fuzzy logic method in which seven areas were identified such as Sargaz Kuh copper mine, Hossein Abad manganese mine, and Esfandagheh iron mine. Results showed the possibility of establishing mineral exploration model and producing mineral potential map in reconnaissance and prospecting stages using appropriate sensors and image processing techniques.

Due to improvements in remote sensing techniques and available analyzes it is now possible to prepare maps of lithology and alteration of an area. In this study, Aster image as well as several image classification (Maximum likelihood(MLC), Spectral Angle Mapper(SAM) and Spectral Information Divergence(SID)) were used to provide lithology maps and spectrum of minerals has been applied for the enhancing of alterations. To evaluate the accuracy of the prepared geologic maps were used. The classification results showed that the MLC method has the highest accuracy and the classified image using this method is acceptable. Also, spectrum of minerals which obtained by FieldSpec3 Analytical Spectral Device (ASD) were utilized to prepare the alteration map using Mixture Tuned Matched Filtering (MTMF) method. The presence of sericite and chlorite minerals were confirmed by examination of thin sections. The obtained lithological and alteration maps represent that the phyllic zone associated with granite and granodiorite rocks, while argillic and propylitic zones are mostly accompanied with andesitic rocks of study area.

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 Zarshuran gold area, and as a result, the alteration zones in the area have been identified. Then, the results of two-dimensional and three-dimensional modeling of Induced Polarization (IP) and resistivity data, using geological information, alteration and mineralization from the core drilling have been interpreted. Eventually, optimal locations for exploratory drilling have been proposed.

Development of advanced tools in remote sensing and geophysical exploration during recent decades indicates the necessity and importance of these tools in industry. In this paper, ASTER sensor imagery and geoelectrical data have been used in order to determine alteration zones, analyze mineralization system and identify the hidden mineralization in Zarshuran gold mine located in the north of the city of Takab, northwest of Iran. For this purpose, a variety of imageprocessing methods are used. IP and resistivity methods have an important role for exploration of metallic ore deposits. To achieve good results from these methods as well as minimizing the noise in the study area, it is necessary to select appropriate electrode array type for carrying out IP and resistivity surveys. For this purpose, IP and resistivity field operations over 17 parallel survey lines using the pole-dipole array have been made to identify the location of goldmineralization in the area.

In order to identify alteration zones, image processing methods such as BR (band ratio), PCA (principal component analysis), LS-Fit (linear band prediction) and SAM (spectral angle mapping) using ENVI software were applied on the ASTER images from the study area. After collecting IP and resistivity data in the area, two-dimensional and threedimensional smooth inverse modeling were carried out on the data using Res2dinv and Res3dinv software packages, and for better visualization, the results were demonstrated in Voxler and Rock Works software packages.

Identification of alteration zones in the study area using remote sensing and image processing methods, and interpretation of the geophysical inverse modeling results using geological and drilling information in the area have been led to the identification of gold mineralized zones or deposits in three-dimensional form. Eventually, based on the whole results, optimal locations for exploratory drilling have been proposed. An outcome of this research is that applying both the remote sensing and geophysics data can be led to improve the accuracy of the results. As the obtained geophysical anomalies at the end of some survey lines have been open, therefore, it is suggested to continue geophysical operations at the end of these survey lines. For better display of gold mineralization, it is also recommended to carry out geophysical operations on a number of survey lines perpendicular to main parallel survey lines. As the acquired considerable IP values in the study area can be due to metallic minerals as well clay minerals, therefore, it is recommended that some samples to be taken from drillings or excavations in the area, and then, to be analyzed by x-ray diffraction (XRD) equipment to determine the amount and type of possible metallic or clay minerals in the samples.

Dividing the structural ones, the studied area has been located in the central Iran and in Makmaei Uromieh- Dokhtar zone. This range has been located in a scene ETM No. 164 - 37 and ASTER linear bad prediction satellite image No. AST_L1A:002:ASTL1A 0108220733380109011021. Such measured images in different band combinations will be used for extracting the geological structures and types of alterations (iron oxide, Argillite and Carbonate) and for detecting different stones and minerals of the ground, a spectrum range of 1.5 to 2.5 μ is very important. This range includes short to average IR range covering six linear band predictions (SWTR bands). According to results of XRD analysis, Albite, andradite, chlorite, gibbsite and Moscuit minerals and silica alterations were also dissociated. On the other side, to use spectral reflectance curves of such minerals in USGSENVI spectral library for spectral analysis, it is necessary to resample the curves to the spectral range of ASTER. Linear Band Prediction methods, LS-Fit, Matched Filtering and BandRATIO used of ASTER images for all minerals and iron alterations and for iron oxides there were also used visual interpretations and ETM images were used in band combination of RGB:531. The resalts identified in the remote sensing study in the aera (Kamoo) identide as follows : Alteration of iron (Gotit, Hematit and jarosit and limotit), alteration of argilic (maolinite, mottmoriolotit, ilite and halozite), carbonate (calcite and dolomite)

Summary: In this study, satellite images, and aeromagnetic and ground magnetic data were analyzed to explore the geothermal potential in Sirch-Golbaf area in Kerman province. Thermal anomalies and apparent thermal inertia images were studied using MODIS, Landsat and ASTER images. As a result, two thermal anomalies were obtained; one in the southeastern part of the study area and the other one in Jooshan location. Magnetic investigations also detected two anomalies; a deep magnetic anomaly in the southern part of the area and another magnetic anomaly near Jooshan hot spring in the northeastern part. These magnetic anomalies were correlated with thermal anomalies.
Remote sensing techniques are helpful reconnaissance tools for detecting surface temperature anomalies and identifying geothermal indicators (Calvin et al., 2005). Lu et al. (2008) used Landsat ETM thermal images to detect thermal anomalies strongly correlated with faults in certain scales in the Jiangshan-Shaoxing fault in the Zhejiang Province, China. They defined thermal anomalies as areas having temperatures higher than the temperature of the spatial background. In a geothermal resource exploration in Akita and Iwate prefectures, northern Japan, Noorollahi et al. (2007) showed that 95% of the production wells were located in a zone within 6000 m to the active faults and 4000 m to hot springs. Magnetic measurements are also generally used in geothermal exploration programs to locate hidden intrusive bodies and possibly estimate their depths. Moreover, they can be used to trace buried dykes and faults, and also to detect areas of reduced magnetization due to thermal activity (Georgeson, 2009). A variety of magnetic studies in geothermal exploration projects having different objectives can be found in the literature (e.g. Hojat et al., 2016; Gailler et al., 2014; Georgsson, 2009; Hunt, 1989; Palmason, 1975). The aim of this study is to analyze remote sensing and magnetic data (airborne and ground measurements) for evaluating the geothermal potential zones in an area east of Kerman Province.
Methodology and Approaches: The input data in this research include MODIS, MOD11_L2 005 (day and night) reflectance and LST products, for the year 2015, ASTER L1T night-time image on November 10, 2015, Landsat ETM day-time image on November 14, 2015, aeromagnetic data collected by Houston Texas Co., USA, in 1975-1977, and geomagnetic total intensity contour map of Gowk area having 1:50000 scale, which surveyed by Atomic Energy Organization of Iran. Ground magnetic survey is also carried out in an area around Joshan hot spring. A comparison of the day-time and night-time images can reveal surface thermal differences for detecting geothermal anomalies. Land surface temperature was calculated using generalized split-window algorithm for MODIS sensor (Wan and Dozier, 1996), emissivity normalization method for ASTER (Coll et al., 2007; Banerjee et al., 2014), and LST calculation method for Landsat sensor (Barsi et al., 2003; Barsi et al., 2005; Coll et al., 2010). Apparent thermal inertia of the three sensors was calculated using albedo and LST difference of day and night (Sabol et al., 2006; Scheidt et al., 2010; Chang et al., 2012; Qin et al., 2013). After removal of noise from the observed magnetic data, processing steps including main field removal using IGRF model of the proper period, reduction to the pole, and upward continuation were applied on the magnetic data. The processed magnetic data were finally interpreted in order to locate the hidden intrusive bodies and faults.
Results and Two thermal anomalies were detected on the maps and charts obtained for the average temperature difference (day and night) and apparent thermal inertia. One anomaly was located in the Jooshan area and the other one was situated in the western part of Gowk fault and continues along it to the southeastern side. Gowk fault is an active fault with Jooshan (45 C) hot spring, and most earthquakes larger than magnitude 5 have occurred in this part. These might be evidences of a thermal anomaly. The results of magnetic interpretations confirmed thermal anomalies showing a deep magnetic anomaly in the southern part of the study area and another magnetic anomaly in the Jooshan hot spring.

The study area is located about 220 km southwest of Mashhad and 80 km south of Neyshabur, at 54° 42' 15" to 54° 43' 40" longitude. Initially, remote sensing is carried out based on the SAM method and it denotes propylitic, carbonitization, silicification and argillic alterations. This area comprises of outcrops of Paleocen-Eocene volcanics. Golcheshmeh area also shows copper mineralization at surface such as malachite, chrysocolla and chalcocite. The copper minerals are seen as filling voids and thin veinlets in association with volcanic rocks in the study area. In some parts of the district, the movement of copper solutions is controlled by linear structures and fault zones, and the amount of solutions’ penetration-which differs from a few centimeters to several meters - in the host rocks is dependent on the wall rock composition, texture and the volume of the solutions. Based on the analysis, 80% of the samples show more than 1% copper.

The study area is located at 42 km NE of Qorveh city, in Kordestan Province and in the Metamorphic– Magmatic Sanandaj-Sirjan Zone. There are other important gold mines such as the Zarshouran and Aghdarreh mines in this zone. The most important alterations of the region are sericitic (phyllic), argillic, silicification and propylitic respectively. Therefore, in this research, the phyllic and argillic alterations were the main purpose and by using different techniques of images processing of satellite images such as: False Color Composition, Band Ratio, Principal Component analysis, Crosta and finally by Spectral Angle Mapper methods iron oxides and development of alterations have been recognized. For accuracy between field evidences and results of software processing, X-Ray Diffraction analysis were used for controlling and recognizing the index minerals of each zone. Then, the comparison between standard and the study area curves were done to confirm the obtaining results. Finally, this method was effective in recognizing and mapping of the hydrothermal alterations.

The studied area is located in east of Bajestan Township, Khorasan Razavi Province and this region is a part of the Lut Block. Granite is the mostimportant rock in this area with covering approximately 70km2. Processing of satellite data in this area was done by using of SPOT, ASTER and Landsat ETM+ data. SPOT images processing and using PCA methods (standard and selective) on the ETM+ data show this intrusive body doesn’t have an equal chemical composition. The central part of the intrusive body has distinctive from margin and it seems that the central part have more mafic mineral. For enhancing linear structure, high pass, directional, threshold and sobel filters were applied separately and compositional on the SPOT data. By using these filters linear structures became completely obvious and were vectorized digitally. The most of them show northwestern-southeastern trend. ASTER data processing by spectral angle mapper (SAM), band ratio and band composition methods enhanced epidote, sericite, hematite, argilic and silicified alterations. Processing and Interpretation of airborne geophysical data (potassium, thorium, uranium and total magnetic intensity), which collected by airplane show the amounts of these triple elements (K,U,Th) are high and in vice versa Total Magnetic Intensity data (TMI) is low in this granite. Separating geological boundaries and enhancing major faults are other results from processing of geophysics data. Merging all of the data consist of: satellite and geophysics data processing and field research indicate alteration zones have relation to linear structures in this area. This research specifies the most probability of mineralization presence in this area so that Fe and Cu mineralization conform to epidotic-chloritic and argilic alterations. Introducing favorable area can help us to concentrate exploration activities and next researches in this area and prevent wasting money and time.

Development of advance tools in remote sensing and airborne geophysics during recent decades shows this industry importance. In this paper, aster sensor imagery (Advanced Space born Thermal – Radiometer) and airborne geophysics employed in order to zoning alteration area, mineralization system analysis and prospecting in 1:25000 Oghlansar sheet, which is situated in north of Sarab City in East Azerbaijan province. The area is located in structural zone of the Eastern Alborz-Azerbaijan. The lithology of area contains Eocene-Neogene magmatic-volcanic complex such as andesite, rhyodacite, rhyolite, and granodiorite associated with pyroclastics such as tuffs, volcanic breccia and lava flows. In this investigation, we applied different methods of spectral analysis and normal classification such as SAM (Spectral Angel mapping), MF (Match Filtering) using ASTER images. Furthermore, spectral analysis methods on airborne geophysics data were engaged in order to extract shallow bodies and recognition of faults. ASTER imagery process and airborne geophysics data led to primary potential mineral map of the area. For credibility of results, 200 samples were taken and analyzed by XRD, XRF and ICP methods. Consequently, 190 samples (95%) confirmed the results of remote sensing and airborne geophysics processes. Conclusions of this research revealed that applying concurrency both the remote sensing and airborne geophysics data could be led to improve the precision of the results.