Advanced Spaceborne Thermal Emission And Reflection Radiometer Data Research Articles

Mapping Hydrothermal Zoning Pattern of Porphyry Cu Deposit Using Absorption Feature Parameters Calculated from ASTER Data

Identifying hydrothermal zoning pattern associated with porphyry copper deposit is important for indicating its economic potential. Traditional approaches like systematic sampling and conventional geological mapping are time-consuming and labor extensive, and with limitations for providing small scale information. Recent developments suggest that remote sensing is a powerful tool for mapping and interpreting the spatial pattern of porphyry Cu deposit. In this study, we integrated in situ spectral measurement taken at the Yudai copper deposit in the Kalatag district, northwestern China, information obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), as well as the spectra of samples (hand-specimen) measured using an Analytical Spectral Device (ASD) FieldSpec4 high-resolution spectrometer in laboratory, to map the hydrothermal zoning pattern of the copper deposit. Results proved that the common statistical approaches, such as relative band depth and Principle Component Analysis (PCA), were unable to identify the pattern accurately. To address the difficulty, we introduced a curve-fitting technique for ASTER shortwave infrared data to simulate Al(OH)-bearing, Fe/Mg(OH)-bearing, and carbonate minerals absorption features, respectively. The results indicate that the absorption feature parameters can effectively locate the ore body inside the research region, suggesting the absorption feature parameters have great potentials to delineate hydrothermal zoning pattern of porphyry Cu deposit. We foresee the method being widely used in the future.

Twenty Years of ASTER Contributions to Lithologic Mapping and Mineral Exploration

The Advanced Spaceborne Thermal Emission and Reflection Radiometer is one of five instruments operating on the National Aeronautics and Space Administration (NASA) Terra platform. Launched in 1999, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has been acquiring optical data for 20 years. ASTER is a joint project between Japan’s Ministry of Economy, Trade and Industry; and U.S. National Aeronautics and Space Administration. Numerous reports of geologic mapping and mineral exploration applications of ASTER data attest to the unique capabilities of the instrument. Until 2000, Landsat was the instrument of choice to provide surface composition information. Its scanners had two broadband short wave infrared (SWIR) bands and a single thermal infrared band. A single SWIR band amalgamated all diagnostic absorption features in the 2–2.5 micron wavelength region into a single band, providing no information on mineral composition. Clays, carbonates, and sulfates could only be detected as a single group. The single thermal infrared (TIR) band provided no information on silicate composition (felsic vs. mafic igneous rocks; quartz content of sedimentary rocks). Since 2000, all of these mineralogical distinctions, and more, could be accomplished due to ASTER’s unique, high spatial resolution multispectral bands: six in the SWIR and five in the TIR. The data have sufficient information to provide good results using the simplest techniques, like band ratios, or more sophisticated analyses, like machine learning. A robust archive of images facilitated use of the data for global exploration and mapping.

LITHOLOGICAL MAPPING USING LANDSAT 8 OLI AND ASTER MULTISPECTRAL DATA IN IMINI-OUNILLA DISTRICT SOUTH HIGH ATLAS OF MARRAKECH

Abstract. This study exploited the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) data in order to map lithological units and structural map in the south High Atlas of Marrakech. The method of analysis was used by principal component analysis (PCA), band ratios (BR), Minimum noise fraction (MNF) transformation. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. SVM based on ground truth in addition to the results of PCA and BR show an excellent correlation with the existing geological map of the study area. Consequently, the methodology proposed demonstrates a high potential of ASTER and Landsat 8 OLI data in lithological units discrimination. The application of the SVM methods on ASTER and Landsat satellite data show that these can be used as a powerful tool to explore and improve lithological mapping in mountainous semi-arid, the overall classification accuracy of Landsat8 OLI data is 97.28% and the Kappa Coefficient is 0.97. The overall classification accuracy of ASTER using nine bands (VNIR-SWIR) is 74.88% and the Kappa Coefficient is 0.71.

Comparative Study of Atmospheric Correction Methods of ASTER Data to Enhance the Delineation of Uranium Mineralized Zones

Multispectral imaging sensors are utilized to discover and identify various surface materials, topographical and geological features. Also it is a used to differentiate lithological units and to provide mineral maps. Although successful processing methodologies have been developed for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery for mineral exploration and geological mapping. Questions still arise regarding the optimal atmospheric correction for these applications. This article provides an outline and an evaluation of existing atmospheric compensation algorithms applied on the visible and shortwave infrared spectral region. This may assist in developing a uranium exploration program using ASTER imagery by delineation of the altered minerals associated with the uranium mineralization

Regional scale prospecting for non-sulphide zinc deposits using ASTER data and different spectral processing methods

ABSTRACT The Ravar-Kuhbanan-Bahabad belt (RKBB) in Central Iran contains several carbonate-hosted non-sulphide Zn (zinc)-Pb (lead) deposits. The Gujer Zn mine area located in the middle of the RKBB was selected as the case study. Due to its large extent, dolomitic envelope in carbonate host rocks can be considered as a more appropriate exploratory target than small Zn-rich gossans or blind karst filling ore. Based on previous studies, the occurrence of red sandstone as a candidate of supplying metal for mineralization and evaporate as sulphate source for mineralized liquids in the vicinity of carbonate rocks can be important exploratory key in the RKBB. Non-sulphide Zn deposits were formed through oxidation of primary Mississippi Valley-type (MVT) deposits in the study area. Remote sensing studies were undertaken using visible to near-infrared (VNIR) and shortwave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the objective of lithological mapping. Five traverse lines containing a total of 81 samples were designed and followed with subsequent chemical analysis, thin section studies, and spectroscopy to verify the results. Two types of carbonates, namely, magnesian dolomite as host rock and surrounding calcitic limestone, were realized through using magnesium oxide (MgO) to calcium oxide (CaO) ratio. Based on spectroscopy studies, calcite and dolomite showed distinct absorption features at 2.35 µm and 2.32 µm, respectively, in ASTER band 8 while a shoulder at 2.25 µm was seen in ASTER band 7 for dolomite. Three image processing methods including spectral angle mapper (SAM), linear spectral unmixing (LSU), and mixture-tuned matched-filtering (MTMF) were applied to separate dolomite and limestone. The accuracy of image classification was numerically estimated using a confusion matrix. Limestone with the accuracy of 95.83% was more precisely enhanced using MTMF method compared to SAM and LSU methods. Highest accuracy of 75% for dolomite was obtained through using LSU method. Red sandstone and evaporate units were classified using MTMF and SAM/LSU methods, respectively. Rock units with the highest accuracy were selected and simply overlain on an image of ASTER in a GIS platform to create the potential map of the study area. Results showed that ASTER data can be successfully used to prepare a potential map for regional scale prospecting for carbonate-hosted non-sulphide Zn-Pb deposits in geological setting and climate condition similar to the RKBB.

Partial sub-pixel and pixel-based alteration mapping of porphyry system using ASTER data: regional case study in western Yazd, Iran

ABSTRACT This study uses remote sensing image-processing to enhance recognition of areas with mineral abundance halo, which can be associated with porphyry mineralisation of the Urumieh-Dokhtar Magmatic Belt (UDMB) in western Yazd. Granitoid intrusions of Oligocene-Miocene age in UDMB hosts the most important Porphyry Copper Deposits (PCDs) of Iran such as Darezereshk and Aliabad PCDs. Diagnostic spectral absorption features of six shortwave infrared (SWIR) and three visible and near-infrared (VNIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were applied to determine the alteration minerals and their abundance. In this research reflectance data from various representative alteration types throughout the study area were measured by the FieldSpec-3 spectroradiometer and applied for mapping minerals. Different remote sensing analytical techniques, including the Principal Component Analysis (PCA), band ratio, relative absorption band depth, and MTMF, were applied to enhance mapping the alteration minerals. Field works including rock sampling, petrography and field spectroradiometer followed up the alteration mapping. Field observation implies that, the vein-type mineralisation above the cupola of this porphyry system is preserved in the western part, although it was eroded in the eastern area. Consequently, PCDs potential is expected to be higher in the western area.

Detecting daytime and nighttime land surface temperature anomalies using thermal infrared remote sensing in Dandong geothermal prospect

Traditional ground survey methods have limited the development and use of renewable energy from geothermal resources. In this paper, the geothermal potential area of Dandong, China is studied using the thermal infrared (TIR) remote sensing data from daytime Landsat 8 and nighttime Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Through pre-processing such as georeferencing, radiometric calibration, and atmospheric correction, the Landsat8 TIRS and ASTER data were used to invert the land surface temperature of the study area during the daytime and nighttime using the single-channel algorithm and temperature and emissivity separation algorithm. Furthermore, the land surface temperatures during daytime and nighttime of three natural land features—water, vegetation, and bare soil—were classified and analyzed. According to the results, vegetation and bare soil show relatively thermal anomalies during the day and relatively cold anomalies during the night. Conversely, water shows relatively cold anomalies during the day and relatively thermal anomalies during the night. Calculating the daytime and nighttime mean of land surface temperature (DNMLST) can eliminate the relatively cold/thermal anomalies exhibited by natural land features during the daytime and nighttime while highlighting the geothermal anomaly zone. Nine geothermal anomaly zones were identified using the threshold method. The auxiliary analysis of geological data excluded non-geothermal effects. Studies have shown that the distribution of the identified geothermal prospects is consistent with the development and distribution of faults. The fractures cut the land surface, causing groundwater to form structural fissure hot water through fracture structures and fissures after magma heating. The use of two higher-resolution TIR remote sensing data products to obtain the DNMLST for the detection of geothermal anomalies has proven cost-effective technical method.

Detection of ground thermal anomaly under dense vegetation based on ASTER TIR images

Ground thermal anomalies associated with geothermal surface manifestations such as hot springs, fumaroles, altered surfaces, and steaming grounds serve as crucial indicator for geothermal explorations. In order to highlight the ground thermal anomalies, this study was raised to use the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to estimate surface temperature under condition of dense vegetation. This study was focused to exploit the ASTER Thermal Infrared Radiometer (TIR) under lab and field scale conditions. The ASTER TIR bands were used to extract the Land Surface Temperature (Ts) from radiances by excluding surface emissivity (εs). The ε is a surface parameter dependent to the surface materials. In this paper, we demonstrated the performance of the Normalized Emissivity Method (NEM) to calculate the Ts by estimating the ε under condition of dense vegetation. The Patuha and Wayang Windu Geothermal field in West Java (Indonesia) were selected as study site due to existence of surface manifestations under canopy vegetation and open area. According to the method, we identified that the ground thermal anomalies are located at surface manifestations. Due to the different spatial scales of satellite and surface measurements and the lack of homogeneous areas, which are representative for low resolution pixels and ground measurements, ground-validation is necessary. The consistency between ASTER data and location of geothermal manifestations indicated that thermal remote sensing data integrated with a spatial-based model, provides an effective means for identifying geothermal potential.

Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area

Land cover has a strong effect on the evapotranspiration (ET) and the hydrologic cycle. Urbanization alters the land cover affecting the surface energy balance and ET by, for example, urban encroachment in agricultural areas. This study investigates the potential utility of high resolution ET in determining more accurately the impact of land cover on water use for an agricultural area. The approach was to apply the physically based two-source energy balance (TSEB) model to very high resolution (~8 m) aircraft thermal data and compare the ET pattern and distribution to TSEB output using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired on 2 August 2012. Modeled flux components were validated using measurements collected from a network of 16 eddy covariance (EC) towers at the study site. The modeled ET using the aircraft data agreed satisfactorily with the flux tower measurements and had better performance than the TSEB model applied to the ASTER data. The percent errors between ET closed by the Bowen ratio (BR) and residual (RE) approaches were 3 and 1%, respectively. It is shown that the high resolution aircraft ET can more accurately determine the change in ET magnitude by having pure pixels of the main land cover types, namely urban, agriculture, and natural vegetation. As a result, the ET histogram exhibits a significant bi-modal distribution which can be used to accurately distinguish the impact on ET from urban versus agricultural land cover areas and potentially monitor the effect on ET over a landscape due to small changes in land cover. At the coarser 90 m resolution of ASTER, the TSEB ET estimates are more often a combination of urban and agricultural land cover ET near the urban-agriculture land cover boundaries. As a result, the bi-modal distribution in ET is almost nonexistent. This study demonstrates the potential utility of high resolution ET mapping for more accurately determining the magnitude of the ET differences between cropland and urban land cover. It also suggests that, with high resolution thermal imagery, TSEB is a potential tool for monitoring the impact on ET due to relatively small changes in land cover as a result of urban expansion. Such a tool would be useful for watershed management.

Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods

ABSTRACTLithological mapping using satellite images, particularly the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data help in effectively defining the best initial targets for regional exploration. ASTER data allow for the discrimination of rock units in the broader region. This research work is focused on the use of remote sensing techniques for geological mapping using ASTER satellite image and generating a geological map of Sangan region. The study area is located in southeast of Khorasan-e-Razavi province and at the eastern edge of the Khaf-Kashmar-Bardskan Volcano-Plutonic Metallogenic Belt in northeast Iran. Band ratio (BR), spectral angle mapper (SAM) and support vector machines (SVMs) methods were used for classifying the main lithologic units in Sangan region. The results of BR, SAM and SVM techniques were quantitatively compared with geological boundaries mapped in the field showing an accuracy of nearly 79 %. SVMs method, in comparison to conventional methods of classification, was known to provide superior results. As the final result of this research, integration of remote sensing and field investigations led to generating high accuracy geological map in the Sangan region. Application of the methods has invaluable implications for geological mapping and mineral exploration in inaccessible regions.

Integration and Visualization of Mineralogical and Topographical Information Derived from ASTER and DEM Data

This paper proposes a method of combining and visualizing multiple lithological indices derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and topographical information derived from digital elevation model (DEM) data in a single color image that can be easily interpreted from a geological point of view. For the purposes of mapping silicate rocks, carbonate rocks, and clay minerals in hydrothermal alteration zones, two new indices derived from ASTER thermal infrared emissivity data were developed to identify silicate rocks, and existing indices were adopted to indicate the distribution of carbonate rocks and the species and amounts of clay mineral. In addition, another new method was developed to visualize the topography from DEM data. The lithological indices and topographical information were integrated using the hue–saturation–value (HSV) color model. The resultant integrated image was evaluated by field survey and through comparison with the results of previous studies in the Cuprite and Goldfield areas, Nevada, USA. It was confirmed that the proposed method can be used to visualize geological information and that the resulting images can easily be interpreted from a geological point of view.

Porphyry Copper Potential of the United States Southern Basin and Range Using ASTER Data Integrated with Geochemical and Geologic Datasets to Assess Potential Near-Surface Deposits in Well-Explored Permissive Tracts

AbstractArcGIS was used to spatially assess and rank potential porphyry copper deposits using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data together with geochemical and geologic datasets in order to estimate undiscovered deposits in the southern Basin and Range Province in the southwestern United States. The assessment was done using a traditional expert opinion three-part method and a prospectivity model developed using weights of evidence and logistic regression techniques to determine if ASTER data integrated with other geologic datasets can be used to find additional areas of prospectivity in well-explored permissive tracts. ASTER hydrothermal alteration data were expressed as 457 alteration polygons defined from a low-pass filtered alteration density map of combined argillic, phyllic, and propylitic rock units. Sediment stream samples were plotted as map grid data and used as spatial information in ASTER polygons. Gravity and magnetic data were also used to define basins greater than 1 km in depth. Each ASTER alteration polygon was ranked for porphyry copper potential using alteration types, spatial amounts of alteration, stream sediment geochemistry, lithology, polygon shape, proximity to other alteration polygons, and deposit and prospects data. Permissive tracts defined for the assessment in the southern Basin and Range Province include the Laramide Northwest, Laramide Southeast, Jurassic, and Tertiary tracts. Expert opinion estimates using the three-part assessment method resulted in a mean estimate of 17 undiscovered porphyry copper deposits, whereas the prospectivity modeling predicted a mean estimate of nine undiscovered deposits. In the well-explored Laramide Southeast tract, which contains the most deposits and has been explored for over 100 years, an average of 4.3 undiscovered deposits was estimated using ASTER alteration polygon data versus 2.8 undiscovered deposits without ASTER data. The Tertiary tract, which contains the largest number of ASTER alteration polygons not associated with known Tertiary deposits, was predicted to contain the most undiscovered resources in the southern Basin and Range Province.

Monitoring thermal anomaly and radiative heat flux using thermal infrared satellite imagery – A case study at Tuzla geothermal region

Geothermal energy, which is renewable, reliable and environmentally friendly, is one of the most important energy resources. Thus, it is crucial to explore geothermal areas in order to reduce the use of other energy sources that are detrimental to the environment and ecology. Thermal Infrared (TIR) remote sensing is an effective way to detect thermal anomalies in geothermal areas and volcanoes, since it is cost and time effective, and offers to work on a large scale compared to geophysical methods. The aim of this study is to investigate thermal anomalies in Tuzla geothermal region using daytime and nighttime TIR data with reference to Land Surface Temperature (LST) and Radiative Heat Flux (RHF). Many geophysical studies have been conducted in this region; however, it can also be studied with TIR remote sensing for further exploration. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired on 15.06.2012 and 15.07.2017 as daytime image and 15.09.2013 and 31.12.2017 as nighttime image, were utilized as satellite imagery. In addition to ASTER data, we proposed a multi-sensor based LST retrieval for nighttime using Landsat 8 data for emissivity acquisition. In order to evaluate the accuracy of LST images, cross-validation method was utilized with reference to Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The coefficient of determination (r2) and Root Mean Square Error (RMSE) were considered as statistical metrics and the lowest result was obtained as 90% and 1.76 K, respectively. As a result of the analyses, it was observed that nighttime LST presented better results for thermal anomalies in that geothermal area than daytime LST. Considering geothermal anomaly, the geothermal area had higher LST values even though it held identical or same NDVI values as compared to non-geothermal surroundings. In addition, the net radiative heat loss values were calculated as 17.83 MW and 121.28 MW for 2013 and 2017, respectively. The obtained results proved that TIR remote sensing could be utilized in the studies of geothermal area exploration.

Investigating the capabilities of multispectral remote sensors data to map alteration zones in the Abhar area, NW Iran

ABSTRACT Economic mineralization is often associated with alterations that are identifiable by remote sensing coupled geological analysis. The present paper aims to investigate the capabilities of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat-8 and Sentinel-2 data to map iron oxide and hydrothermally alteration zones in the Abhar area, NW Iran. To achieve this goal, the principal component analysis (PCA) and two machine learning methods including support vector machine (SVM) and artificial neural network (ANN) were employed. PCA method was carried out on four bands of all data and then the appropriate principal components were selected to map alterations. Due to the high precision of ASTER data within the short-wave infrared range, these data results are more satisfactory compared with Landsat-8 and Sentinel-2 sensors in detecting hydrothermally alterations through the PCA technique. Based on the obtained maps, the performance of all data types was approximately similar in the detection of iron oxide zones. Our desired data were classified by two methods of SVM and ANN. The results of these algorithms were presented as confusion matrix. According to these results, for hydrothermally alterations, ASTER data showed better performance in both SVM and ANN than other datasets by gaining values greater than 90%. These data did not perform well in the iron oxide zones detection, while Landsat-8 and Sentinel-2 have been more successful. For iron oxide, based on confusion matrix, Landsat-8 data have obtained the values of 78% and 79% through SVM and ANN algorithms, respectively, and also Sentinel-2 has acquired the values of 88.11% and 90.55% via SVM and ANN, respectively. Therefore, to map iron oxide zones, Sentinel-2 data are more favorable than Landsat-8 data. In addition, the ANN algorithm in ASTER data has represented the highest overall accuracy and Kappa coefficient with the values of 88.73% and 0.8453, respectively.

Utilization of ASTER and OLI data for lithological mapping of Nugrus-Hafafit area, South Eastern Desert of Egypt

Lithological discrimination of Neoproterozoic rocks occupying Nugrus-Hafafit area, South Eastern Desert of Egypt, has been carried out using Operational Land Imager (OLI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors’ imagery data. The applicable processing enhancement techniques include optimum index factor (OIF), band ratioing, principal component analysis (PCA), and minimum noise fraction (MNF) transform. The area comprises varieties of low-grade metamorphosed ophiolitic melange and island-arc rocks, thrusting over high-grade metamorphic gneissic core complexes, and intruded by syn-, late-, and post-tectonic granitoids. The OLI band ratio 6/7 discriminates clearly the ophiolitic serpentinites-talc-carbonate rocks, while 4/5 ratio image is able to separate between mafic and felsic rocks. Moreover, the ASTER band ratio 6/8 is used to distinguish the amphibole-bearing rocks, including amphibolite and hornblende gneiss. The OLI and ASTER second principal component (PC2) images reflect the contrast spectral behavior of ophiolitic melange rocks through visible-near-infrared (VNIR) and shortwave (SWIR) regions. The OLI-PC3 shows the ability to delineate the Fe-rich rocks, including amphibolite and metamafics, while ASTER-PC3 is effective for quartz-feldspathic granites and psammitic gneisses. Visual interpretation and integration of processed data with petrography and field investigation resulted in complete differentiation for the different lithologies and creation of a new detailed geological map of Nugrus-Hafafit area.

IDENTIFICATION OF ROCKS AND THEIR QUARTZ CONTENT IN AMARKANTAK, INDIA USING ASTER TIR DATA

Abstract. Quartz (SiO2) abundance in rock is an important indicator of mineralization in many metal deposits and quartz detection has a great role in mineral exploration. The present study identified the quartz contained rocks in Amarkantak region, India applying thermal infrared bands (bands 10–14) of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image. After atmospheric correction, principal component analysis technique was applied on the TIR bands and the resulting principal component images were analyzed. The three optimal principal components were selected based on the spectral interaction strength and the eigenvalues of each band of the ASTER data. The result presented that extrusive igneous rock and carbonate sedimentary rocks are quartz-poor while sedimentary rocks made up of organic particles and sandstone is quartz-rich.

Application of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral imagery to mineral and lithologic mapping in southern West Greenland

Remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used for mineral and lithologic mapping at the Sarfartoq carbonatite complex area in southern West Greenland. The geology of the study area consists of carbonatites, fenites, hydrothermal alteration zones, gneisses, alluvial deposits etc. The Adaptive Coherence Estimator algorithm was used to analyze the remote sensing data. The reference spectra were selected from the imagery. The mapping results show the distribution of carbonatite, hydrothermally altered zones, fenite, and sericite. In addition, lichen and tundra green vegetation were also mapped. Due to the moderate spatial resolution of ASTER SWIR bands, it was not possible to detect and map the rock units in some parts of the study area. The study shows the possibilities and limitations of the use of the ASTER multispectral imagery for geological studies in the Arctic regions of West Greenland. The paper is the first reported study on the use of ASTER data for mineral and lithologic mapping in the Arctic regions of West Greenland.

Delineation of hydrothermal alteration zones for porphyry systems utilizing ASTER data in Jebal-Barez area, SE Iran

The Urumieh-Dokhtar Magmatic Belt (UDMB) is the host of many Iranian Cu porphyry deposits. The southern part of this belt, in the Jebal-Barez area, has been less investigated due to the mountainous and rough topography as well as some security confrontations. Porphyry deposits are associated with hydrothermal alteration zones, which can be mapped using the remote sensing data such as Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER). The aim of this study was to identify and detect the alteration zones associated with porphyry systems using ASTER data in Jebal-Barez area, SE Iran. For this reason, seven scenes of ASTER level-1B data which cover the Jebal-Barez area, were pre-processed and then processed by band ratio, false color composite and Spectral Angle Mapper (SAM) methods. The result indicated the presence of extensive phyllic and argillic alteration zones. The argillic alteration is surrounded by border zones of propylitic alteration. Also, a massive granitoid intrusion in NW of the studied area was detected by SAM method and the color composite of 4, 6, and 8 bands of ASTER as a completely altered area (SF area) which strongly needs more detailed exploration and field inspections.

Lithological mapping of East Tianshan area using integrated data fused by Chinese GF-1 PAN and ASTER multi-spectral data

Abstract The East Tianshan Mountain is one of the most important gold ore forming zones in northwestern China and central Asia. The Chinese GaoFen-1 (GF-1), the first Chinese high resolution satellite, is characterized by its 2-m resolution PAN data. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the well-known earth observation satellite, is advanced by its finer spectral resolution owing 9 bands in the visible and near infrared (VNIR) to the short-wave infrared (SWIR) region. In this study, we fused the GF-1 PAN and the ASTER multispectral data using the well-known Gram-Schmidt Pan Sharpening (G-S) method to produce a new data with both high spatial and spectral resolution. Then different lithological units were mapped respectively using the fusion data, the ASTER data and the WorldView-3 data by support vector machine (SVM) method. In order to assess this fusion data, a comparison work was executed among the three mapping results. The comparison work indicated that lithological classification using the new fusion data is an efficient, robust and low cost method, and it could replace the WV-3 data in some large sale geological work.

Validating (MNF) transform to determine the least inherent dimensionality of ASTER image data of some uranium localities at Central Eastern Desert, Egypt

One of the main determinations of geological remote sensing is to develop and improve different image processing algorithms and methods for mineral mapping and rock type discrimination. This paper investigates one of those sophisticated algorithms; the validity of Minimum Noise Fraction (MNF) components to improve the spectral separability of The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor image data of Terra satellite, and to develop a standard method of noise removal and image enhancement. Previous studies that used in image processing to eliminate MNF eigenvalues, eliminate values less than the unit. However, removing MNF eigenvalues more than this value and its effect on the data, has not been examined. Therefore, in this paper, we demonstrate that we can eliminate more than the unit up to 2 eigenvalue without a negative inherent effect on the origin data structure. A comparison study using different Image Quality Measures (IQMs) methods, has been accomplished on data distribution before and after MNF transformation of the original and atmospherically corrected data. Matched Filter (MF) classification was performed on data before and after MNF to map a chosen known alteration mineral (Kaolinite) by matching the image endmember spectra and its spectra from USGS library. By examining the spectral trends of specific mineral alteration type across these transformed channels, areas of interest that are unique by the related previous well-known uranium mineralization may become superficial apparent. This examination also showed how the use of MNF as a pre-processing technique could improve the capability to extract information from ASTER data of El-Missikat, El-Eridya and Kab Amiri areas in the Central Eastern desert as a case study district for uranium mineralization occurrences.