Advanced Spaceborne Thermal Emission And Reflection Radiometer Bands Research Articles

Machine Learning-Based Lithological Mapping from ASTER Remote-Sensing Imagery

Accurately mapping lithological features is essential for geological surveys and the exploration of mineral resources. Remote-sensing images have been widely used to extract information about mineralized alteration zones due to their cost-effectiveness and potential for being widely applied. Automated methods, such as machine-learning algorithms, for lithological mapping using satellite imagery have also received attention. This study aims to map lithologies and minerals indirectly through machine-learning algorithms using advanced spaceborne thermal emission and reflection radiometer (ASTER) remote-sensing data. The capabilities of several machine-learning (ML) algorithms were evaluated for lithological mapping, including random forest (RF), support vector machine (SVM), gradient boosting (GB), extreme gradient boosting (XGB), and a deep-learning artificial neural network (ANN). These methods were applied to ASTER imagery of the Sar-Cheshmeh copper mining region of Kerman Province, in southern Iran. First, several spectral features that were extracted from ASTER bands were used as input data. Second, correlation coefficients between the original spectral bands and features were extracted. The importance of the random forest features (RF’s feature importance) was subsequently computed, and features with less importance were removed. Finally, the remained features were given to the models as input data in the second scenario. Accuracy assessments were performed for lithological classes in the study region, including Sar-Cheshmeh porphyry, quartz eye, late fine porphyry, hornblende dike, granodiorite, feldspar dike, biotite dike, andesite, and alluvium. The overall accuracy results of lithological mapping showed that ML-based algorithms without feature extraction have the highest accuracy. The overall accuracy percentages for ML-based algorithms without conducting feature extraction were 84%, 85%, 80%, 82%, and 80% for RF, SVM, GB, XGB, and ANN, respectively. The results of this study would be of great interest to geologists for lithological mapping and mineral exploration, particularly for selecting appropriate ML-based techniques to be implemented in similar regions.

Mapping of mafic-ultramafic rocks in SMUC-SGT, India using ASTER & Sentinel-2A satellite images

The Salem Mafic–Ultramafic Complex (SMUC) is a major complex in southern Granulite Terrane (SGT), in the northern part of the Cauvery Suture Zone (CSZ), India, also known as the Chalk Hills of Salem. The present study aims to review the efficiency of satellite image processing and related techniques to map the Mafic-Ultramafic rocks in Salem Mafic-Ultramafic Complex (SMUC). This mapping is done using atmospherically corrected Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Sentinel-2A satellite image data. The processes employed were image enhancement techniques like Band Combinations (BC), Principal Component Analysis (PCA), and Minimum Noise Fraction (MNF) to map the various rock types. Band combinations constructed from the output of PCA and MNF in RGB format showed promising results in discriminating various rock units. The Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) classifications techniques were used to classify ASTER and Sentinel-2A satellite images for the study area. The classified lithologies showed strong match with the lithology map published by the Geological Survey of India (GSI), other researches, and field investigation. Particularly, SVM classification of Sentinel-2A MNF + DEM showed 90% overall accuracy when compared with field investigation. The study proved that the processing of VNIR and SWIR bands of ASTER and Sentinel-2A Satellite images coupled with DEM and ground investigation has excellent potential in mapping Mafic-Ultramafic rocks in SMUC SGT.

Application of ASTER Data for Differentiating Carbonate Minerals and Evaluating MgO Content of Magnesite in the Jiao-Liao-Ji Belt, North China Craton

Numerous reports have successfully detected or differentiated carbonate minerals such as calcite and dolomite by using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). However, there is a need to determine whether existing methods can differentiate magnesite from other carbonate minerals. This study proposes optimal band ratio combinations and new thresholds to distinguish magnesite, dolomite, and calcite using ASTER shortwave-infrared (SWIR) data. These were determined based on the spectral and chemical analysis of rock samples collected from Liaoning, China and Danchon, North Korea and the reflectance values from ASTER images. The results demonstrated that the simultaneous use of thresholds 2.13 and 2.015 for relative absorption band depths (RBDs) of (6 + 8)/7 and (7 + 9)/8, respectively, was the most effective for magnesite differentiation. The use of RBDs and band ratios to discriminate between dolomite and calcite was sufficiently effective. However, talc, tremolite, clay, and their mixtures with dolomite and calcite, which are commonly found in the study area, hampered the classification. The assessment of the ASTER band ratios for magnesite grade according to magnesium oxide content indicated that a band ratio of 5/6 was the most effective for this purpose. Therefore, this study proved that ASTER SWIR data can be effectively utilized for the identification and grade assessment of magnesite on a regional scale.

Using reflectance spectroscopy and Advanced Spaceborne Thermal Emission and Reflection Radiometer data to identify bauxite deposits in vicinity of Az Zabirah, northern Saudi Arabia

Bauxite samples from deposits in northern Saudi Arabia were identified in the laboratory using spectral reflectance measurements (at 0.3–2.5 μm) and X-ray diffraction (XRD). The XRD results revealed that the bauxite deposits are composed mainly of goethite, gibbsite, and boehmite with small amounts of kaolinite, hematite, and quartz. The bauxite spectra revealed the presence of significant iron oxides (at 0.5 and 0.87 μm) accompanied by water (at 1.4 and 1.9 μm) and aluminum hydroxide (at 2.2 μm). The convolved Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectra of the bauxite samples were characterized by an aluminum hydroxide feature in ASTER band 6 (at 2.2 μm). The results demonstrated that principal components analysis band PC2 is the best component for delineating the bauxite deposits. Fractional abundances of bauxite were derived by using a matched-filtering method. This study demonstrates the applicability of reflectance spectroscopy and ASTER data to provide spectral information for distinguishing economically important minerals from visible and near-infrared and shortwave-infrared spectra in arid and semiarid environments such as in Saudi Arabia.

Identification of Phyllosilicates in the Antarctic Environment Using ASTER Satellite Data: Case Study from the Mesa Range, Campbell and Priestley Glaciers, Northern Victoria Land

In Antarctica, spectral mapping of altered minerals is very challenging due to the remoteness and inaccessibility of poorly exposed outcrops. This investigation evaluates the capability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite remote sensing imagery for mapping and discrimination of phyllosilicate mineral groups in the Antarctic environment of northern Victoria Land. The Mixture-Tuned Matched-Filtering (MTMF) and Constrained Energy Minimization (CEM) algorithms were used to detect the sub-pixel abundance of Al-rich, Fe3+-rich, Fe2+-rich and Mg-rich phyllosilicates using the visible and near-infrared (VNIR), short-wave infrared (SWIR) and thermal-infrared (TIR) bands of ASTER. Results indicate that Al-rich phyllosilicates are strongly detected in the exposed outcrops of the Granite Harbour granitoids, Wilson Metamorphic Complex and the Beacon Supergroup. The presence of the smectite mineral group derived from the Jurassic basaltic rocks (Ferrar Dolerite and Kirkpatrick Basalts) by weathering and decomposition processes implicates Fe3+-rich and Fe2+-rich phyllosilicates. Biotite (Fe2+-rich phyllosilicate) is detected associated with the Granite Harbour granitoids, Wilson Metamorphic Complex and Melbourne Volcanics. Mg-rich phyllosilicates are mostly mapped in the scree, glacial drift, moraine and crevasse fields derived from weathering and decomposition of the Kirkpatrick Basalt and Ferrar Dolerite. Chlorite (Mg-rich phyllosilicate) was generally mapped in the exposures of Granite Harbour granodiorite and granite and partially identified in the Ferrar Dolerite, the Kirkpatrick Basalt, the Priestley Formation and Priestley Schist and the scree, glacial drift and moraine. Statistical results indicate that Al-rich phyllosilicates class pixels are strongly discriminated, while the pixels attributed to Fe3+-rich class, Fe2+-rich and Mg-rich phyllosilicates classes contain some spectral mixing due to their subtle spectral differences in the VNIR+SWIR bands of ASTER. Results derived from TIR bands of ASTER show that a high level of confusion is associated with mafic phyllosilicates pixels (Fe3+-rich, Fe2+-rich and Mg-rich classes), whereas felsic phyllosilicates (Al-rich class) pixels are well mapped. Ground truth with detailed geological data, petrographic study and X-ray diffraction (XRD) analysis verified the remote sensing results. Consequently, ASTER image-map of phyllosilicate minerals is generated for the Mesa Range, Campbell and Priestley Glaciers, northern Victoria Land of Antarctica.

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.

Reflectance spectroscopy-guided broadband spectral derivative approach to detect glauconite-rich zones in fossiliferous limestone, Kachchh region, Gujarat, India

In this study, we processed visible near-infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to delineate glauconite-bearing zones in fossiliferous limestones, Quaternarysediments and Paleogene shales in the Lakhpat.Region of the Kachchh Province in India. Glauconitic limestone has subtle absorption features at 2.3 µm when compared to the absorption features of pure limestones that are dominated by the strong absorption feature of calcite at 2.33 µm. Additionally, the spectrum of glauconite-rich limestone also has an absorption feature at about 0.9 µm due to the crystal field effect of Fe2+ present in the glauconite structure and a feeble spectral feature due to the presence of Al-OH bonds at about 2.2 µm. ASTER resampled reflectance spectra of these rocks have been used as the reference to construct different image-enhanced products. We derived index images and Eigen matrix analysis-based principal components (PCs), using ASTER bands, to delineate different rocks in the study area. These index images are derived to enhance broadband absorption features observed in shales, glauconite-bearing and pure limestones, respectively. Principal component images are prepared using the spectral bands defining the broadband absorption features of these rocks. We found that the PC image composite, derived using PC 8, PC 2 and PC 7, is suitable to discriminate basalts, limestones and shales from each other, while an index image colour composite, prepared using three independent index images, is suitable for the identification of lithological contacts between Quaternary sediments, shales and fossiliferous limestones, respectively. In addition, the ASTER resampled rock spectrum of glauconite has a relatively lower spectral gradient in comparison to the gradient observed in the spectrum of fossiliferous limestone within the spectral range of bands 6 and 8. The spectral derivative images are derived for discriminating glauconite-rich zones within the limestone using the contrast in the spectral gradient of limestone and glauconite-rich limestone. The image composite of three spectral derivatives was compiled from the derivative image of bands 4 to 3, bands 5 to 7, and bands 6 to 8 to discriminate glauconite-rich zones from pure fossiliferous limestone. Our study proposes the potential use of broadband reflectance spectroscopy in the mineral mapping of sedimentary provinces.

Geospatial assessment of ultramafic rocks and ore minerals of Salem, India

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image interpretation methods such as colour composite images (false colour composite, true colour composite) were adapted to capture the image for interpreting the visible and shortwave infrared raw bands and thus generating the mapping for the ultramafic terrain. ASTER colour composite image generated from shortwave infrared (SWIR) bands 8 and 4 and NIR band 3 shows contrast signature for the presence of rock types in the ultramafic terrain. The low and high silica percentages to be interpreted through the absorption features of the spectral range from 8.1 to 12 μm. The combinations used to map silica index are of bands 10, 11 and 7 as RGB. PCA was applied to SWIR and visible and near-infrared spectral bands and from PCA output PC 6, 2 and 1 used in the generation of RGB colour composite. Hence, the results of PCA processed image highlights the magnesite mining area by dark red colour. The minimum noise fraction transform (B1, B2, B4) in RGB applied to ASTER image to focus on the overlapped rock types inclusive of magnesite and the same achieved as sharp image output. ASTER band ratios (R3/1, G4/5 and B6/8) in RGB calculated in which the numerator represents shoulders of absorption, and the denominator represents nearest absorption band. Thus, this combination indicates clearly the magnesite mining area in blue colour. The relative band depth in thermal infrared (TIR) bands (B13 and B14) correlated to find the carbonate index is high, medium and low through the pixel ratio output of the ultramafic terrain. Preprocessing of ASTER data involved atmospheric correction using FLAASH algorithm. The minimum noise fraction transform reduces the spectral dimensionality of data in a linear combination of bands. Spectral angle mapper and support vector machines are supervised classification technique adopted that are key learning models with the aid of analyse and categorization of data. The classification defends user, producer, overall accuracy and kappa coefficient. The magnesite mining area and adjust rock samples were field observed, and the mapping of the ultramafic terrain supports the output achieved through chosen ASTER band colour composite, band ratios, relative band depth, silica index, PCA, minimum noise fraction and pixel classification. Thus, a more informative lithological map for the ultramafic terrain generated to discriminate magnesite-mining region.

ASTER spectral band ratios for lithological mapping: a case study for measuring geological offset along the Erkenek Segment of the East Anatolian Fault Zone, Turkey

The current work examines the lithological variation along the Erkenek Segment of the East Anatolian Fault (EAF), a major tectonic structure which accommodates the westward extrusion of Anatolia together with the North Anatolian Fault. Mapping the geology at high spatial resolution along this segment with conventional mapping techniques is highly challenging due to the complex tectonic setting and the abundant number of different lithological units of varying spatial extent. Therefore, in the current study, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data along the Erkenek Segment have been used different spectral rationing techniques are applied with band the ratios of 1/3–1/9–3/9, 7/3–1/7–3/5 and 9/5–5/3–3/1 being remarkably useful for detailed lithological mapping and hence detecting the geological offsets along this section of the fault. Thus, these ASTER band ratio images can be used for the lithological mapping along the whole EAF and on other regions in the world with similar lithological and geomorphological conditions.

ASTER and WorldView-3 satellite data for mapping lithology and alteration minerals associated with Pb-Zn mineralization

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and WorldView-3 (WV-3) satellite remote sensing data were used for mapping lithological units and hydrothermal alteration zones associated with Pb-Zn mineralization in the Kerman–Kashmar Tectonic Zone (KKTZ), Iran. The visible near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) bands of ASTER were used to map iron oxide/hydroxides, Al-OH minerals, Fe,Mg-OH minerals, quartz and carbonate minerals. The VNIR bands of WV-3 were used to discriminate Fe3+ and Fe2+ absorption intensities. Selective Principal Component analysis (SPCA), Spectral Angle Mapper (SAM), Linear Spectral Unmixing (LSU) and Automatic Lineament Extraction techniques were implemented. Lithological units were discriminated based on Al/Fe-OH, Fe2+/Fe3+ and Mg-Fe-OH/CO3 absorption properties. The spatial distribution of hematite, goethite, jarosite, gypsum, calcite, dolomite, kaolinite and muscovite were comprehensively detected. Some prospective zones were identified in the intersection of N-S, NW-SE and NE-SW trending fault systems, gossan, argillic/phyllic and dolomitic units.

New logical operator algorithms for mapping of hydrothermally altered rocks using ASTER data: A case study from central Turkey

This study uses logical operator algorithms along with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral reflectance and emissivity data to map hydrothermally altered igneous rocks associated with mineralization around the towns of Hamurcu and Başdere in central Anatolia, Turkey. In addition to band ratios used in previous studies, the logical operator algorithms developed in this work perform multiple mineral indices and directed principal components (DPC) analysis, thereby providing better constraints on the spatial extent of hydrothermally altered rocks around the Hamurcu and Başdere areas. We designed the unique mineral indices and DPC analysis based on the effective use of ASTER bands corresponding to diagnostic spectral absorption features of alteration minerals. The calculation of threshold values of logical operator algorithms is based on a two-stepped statistical approach. The novel logical operator algorithms successfully mapped hydrothermal alteration zones in the study area that include mineral assemblages, such as kaolinite, alunite, sericite, smectite, and ferric iron oxides together with various forms of silica. The Hamurcu area contains altered rocks that display a characteristic alteration pattern of a high-sulfidation epithermal system. On the other hand, alteration minerals are primarily located along the faults in the southern part of the Başdere area. The results of field investigations in conjunction with laboratory spectral reflectance measurements, microscopic examination of thin sections and X-ray diffraction analysis of the samples are quite consistent with ASTER mineral maps derived from the logical operator algorithms from this work. As a result, the new logical operator algorithms implemented to ASTER data of the study area prove to be a powerful tool for generating preliminary, quick, and reliable alteration mineral maps at low cost in similar terrains of different geographic locations.

Reliability of using ASTER data in lithologic mapping and alteration mineral detection of the basement complex of West Berenice, Southeastern Desert, Egypt

The Neoproterozoic basement complex of Egypt outcrops in the Eastern Desert (ED) and southern Sinai, and is regarded to represent the northwestern continuation of the Arabian–Nubian Shield (ANS). The area west of Berenice has been given little attention, although it represents the key to understanding the geologic history of the South Eastern Desert and the entire ED. The present work is an integrated study using remote sensing (Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data imagery) and field-structural data to assess their utility in lithologic mapping and in detecting alteration mineral zones with considerable accuracy. A false-color-composite image, color-ratio composite image, decorrelation stretch, mafic index (MI), and quartz index (QI) were used to discriminate and map the various rock units. Correlation of False-color images of the ASTER band combination (7, 3, 1) with previous lithological mapping studies of the study area allow preliminary discrimination of different lithologies and drawing a base map. Subsequently, ASTER band ratios tested (4/1, 3/1, 12/14) and (4/7, 4/6, 4/10) with the ground truth data were used to refine the base map and construct the digital detailed geologic map. Petrographically, the investigated rock samples show kaolinite, chlorite, and epidote in alteration zones. The spectral angle mapper (SAM)-supervised classification using reference spectra of the USGS spectral library was used for detecting alteration zones. For verification, total accuracy assessment was carried out to evaluate the band combination and band ratios used in the lithologic mapping. That reached to 85.01% for band ratio 4/1, 3/1, 12/14 in RGB.

Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer, and WorldView-3 Multispectral Satellite Imagery for Prospecting Copper-Gold Mineralization in the Northeastern Inglefield Mobile Belt (IMB), Northwest Greenland

Several regions in the High Arctic still lingered poorly explored for a variety of mineralization types because of harsh climate environments and remoteness. Inglefield Land is an ice-free region in northwest Greenland that contains copper-gold mineralization associated with hydrothermal alteration mineral assemblages. In this study, Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and WorldView-3 multispectral remote sensing data were used for hydrothermal alteration mapping and mineral prospecting in the Inglefield Land at regional, local, and district scales. Directed principal components analysis (DPCA) technique was applied to map iron oxide/hydroxide, Al/Fe-OH, Mg-Fe-OH minerals, silicification (Si-OH), and SiO2 mineral groups using specialized band ratios of the multispectral datasets. For extracting reference spectra directly from the Landsat-8, ASTER, and WorldView-3 (WV-3) images to generate fraction images of end-member minerals, the automated spectral hourglass (ASH) approach was implemented. Linear spectral unmixing (LSU) algorithm was thereafter used to produce a mineral map of fractional images. Furthermore, adaptive coherence estimator (ACE) algorithm was applied to visible and near-infrared and shortwave infrared (VINR + SWIR) bands of ASTER using laboratory reflectance spectra extracted from the USGS spectral library for verifying the presence of mineral spectral signatures. Results indicate that the boundaries between the Franklinian sedimentary successions and the Etah metamorphic and meta-igneous complex, the orthogneiss in the northeastern part of the Cu-Au mineralization belt adjacent to Dallas Bugt, and the southern part of the Cu-Au mineralization belt nearby Marshall Bugt show high content of iron oxides/hydroxides and Si-OH/SiO2 mineral groups, which warrant high potential for Cu-Au prospecting. A high spatial distribution of hematite/jarosite, chalcedony/opal, and chlorite/epidote/biotite were identified with the documented Cu-Au occurrences in central and southwestern sectors of the Cu-Au mineralization belt. The calculation of confusion matrix and Kappa Coefficient proved appropriate overall accuracy and good rate of agreement for alteration mineral mapping. This investigation accomplished the application of multispectral/multi-sensor satellite imagery as a valuable and economical tool for reconnaissance stages of systematic mineral exploration projects in remote and inaccessible metallogenic provinces around the world, particularly in the High Arctic regions.

Mapping Listvenite Occurrences in the Damage Zones of Northern Victoria Land, Antarctica Using ASTER Satellite Remote Sensing Data

Listvenites normally form during hydrothermal/metasomatic alteration of mafic and ultramafic rocks and represent a key indicator for the occurrence of ore mineralizations in orogenic systems. Hydrothermal/metasomatic alteration mineral assemblages are one of the significant indicators for ore mineralizations in the damage zones of major tectonic boundaries, which can be detected using multispectral satellite remote sensing data. In this research, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral remote sensing data were used to detect listvenite occurrences and alteration mineral assemblages in the poorly exposed damage zones of the boundaries between the Wilson, Bowers and Robertson Bay terranes in Northern Victoria Land (NVL), Antarctica. Spectral information for detecting alteration mineral assemblages and listvenites were extracted at pixel and sub-pixel levels using the Principal Component Analysis (PCA)/Independent Component Analysis (ICA) fusion technique, Linear Spectral Unmixing (LSU) and Constrained Energy Minimization (CEM) algorithms. Mineralogical assemblages containing Fe2+, Fe3+, Fe-OH, Al-OH, Mg-OH and CO3 spectral absorption features were detected in the damage zones of the study area by implementing PCA/ICA fusion to visible and near infrared (VNIR) and shortwave infrared (SWIR) bands of ASTER. Silicate lithological groups were mapped and discriminated using PCA/ICA fusion to thermal infrared (TIR) bands of ASTER. Fraction images of prospective alteration minerals, including goethite, hematite, jarosite, biotite, kaolinite, muscovite, antigorite, serpentine, talc, actinolite, chlorite, epidote, calcite, dolomite and siderite and possible zones encompassing listvenite occurrences were produced using LSU and CEM algorithms to ASTER VNIR+SWIR spectral bands. Several potential zones for listvenite occurrences were identified, typically in association with mafic metavolcanic rocks (Glasgow Volcanics) in the Bowers Mountains. Comparison of the remote sensing results with geological investigations in the study area demonstrate invaluable implications of the remote sensing approach for mapping poorly exposed lithological units, detecting possible zones of listvenite occurrences and discriminating subpixel abundance of alteration mineral assemblages in the damage zones of the Wilson-Bowers and Bowers-Robertson Bay terrane boundaries and in intra-Bowers and Wilson terranes fault zones with high fluid flow. The satellite remote sensing approach developed in this research is explicitly pertinent to detecting key alteration mineral indicators for prospecting hydrothermal/metasomatic ore minerals in remote and inaccessible zones situated in other orogenic systems around the world.

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.

Emittance Spectroscopy and Broadband Thermal Remote Sensing Applied to Phosphorite and Its Utility in Geoexploration: A Study in the Parts of Rajasthan, India

The contrast in the emissivity spectra of phosphorite and associated carbonate rock can be used as a guide to delineate phosphorite within dolomite. The thermal emissivity spectrum of phosphorite is characterized by a strong doublet emissivity feature with their absorption minima at 9 µm and 9.5 µm; whereas, host rock dolomite has relatively subdued emissivity minima at ~9 µm. Using the contrast in the emissivity spectra of phosphorite and dolomite, data obtained by the thermal bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor were processed to delineate phosphorite within dolomite. A decorrelation stretched ASTER radiance composite could not enhance phosphorite rich zones within the dolomite host rock. However, a decorrelation stretched image composite of selected emissivity bands derived using the emissivity normalization method was suitable to enhance large surface exposures of phosphorite. We have found that the depth of the emissivity minima of phosphorite gradually has increased from dolomite to high-grade phosphorite, while low-grade phosphate has an intermediate emissivity value and the emissivity feature can be studied using three thermal bands of ASTER. In this context, we also propose a relative band depth (RBD) image using selected emissivity bands (bands 11, 12, and 13) to delineate phosphorite from the host rock. We also propose that the RBD image can be used as a proxy to estimate the relative grades of phosphorites, provided the surface exposures of phosphorite are large enough to subdue the role of intrapixel spectral mixing, which can also influence the depth of the diagnostic feature along with the grade. We have validated the phosphorite pixels of the RBD image in the field by carrying out colorimetric analysis to confirm the presence of phosphorite. The result of the study indicates the utility of the proposed relative band depth image derived using ASTER TIR bands for delineating Proterozoic carbonate-hosted phosphorite.

Aster Mapping of Limestone Deposits and Associated Lithounits of Parts of Chikkanayakanahalli, Southern Part of Chitradurga Schist Belt, Dharwar Craton, India

Economically viable limestone deposits are mostly formed by calcite minerals, and these minerals are widely used in manufacturing of cement, mortar, fertilizer and flux for smelting of iron ores, and mapping of such deposits is significant and important in scientific research. This study examines the capability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the wavelength range visible–near-infrared and short-wave infrared spectral bands to map such limestone carbonate deposits and associated lithounits occurred in and around of Chikkanayakanahalli, southern part of the Chitradurga schist belt using minimum noise fraction (MNF) and decorrelation stretching methods. The study results that (1) the RGB image of MNF (R: B1; G: B2; B: B3) of ASTER is capable of discriminating the limestones and associated different rock types, namely banded magnetite quartzites (BMQ), graywackes, Mn- and Fe-rich cherts, metabasalts, granitic gneisses, granitoids and migmatites and (2) the decorrelation stretch image of ASTER bands 8, 3, 1 of the ASTER delineated clearly the limestones and associated rocks of the study area. Study of spectral signatures of field samples of such economic limestones in the wavelength of 350–2500 nm using Fieldspec3 Spectroradiometer showed the spectral absorption near 2.32 μm due to the presence of calcite minerals in the rocks. The results of study are cross-verified in the study area and confirmed through petrological and chemical analyses of the samples. This study bespeaks the potential of ASTER sensor and application of image processing methods to map the economic limestone deposits and associated rocks of the study area.

A semi-empirical approach for the estimation of land-surface emissivity from satellite data based on spectral index fusion using ensemble regression

ABSTRACTLand Surface Emissivity (LSE) is a key parameter in the thermal remote sensing, with several important applications, most notably in Land Surface Temperature (LST) estimation. This paper presents a semi-empirical method of LSE estimation from remote sensing data based on a fusion of spectral indices using the ensemble regression methods. The performance of the proposed method for Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data was evaluated and compared with other semi-empirical methods developed for these sensors. The proposed method was designed in four stages. In the first stage, the reflectance of non-thermal bands and emissivity of thermal bands were simulated for different classes using the ASTER spectral library and the spectral response function of each sensor. In the second stage, the dataset to be used for the training of ensemble regression was arranged by calculating a number of spectral indices, which constitute the feature space along with non-thermal bands. In the third stage, the regression between emissivity of thermal bands of each sensor and the features extracted in the second stage was derived by the use of bagging, boosting and Random Forest (RF) regression methods. In the final stage Using Normalized Difference Vegetation Index (NDVI) values, the image was categorized into three classes including vegetation, non-vegetation and mixture areas using conditions NDVI > 0.5, NDVI < 0.2 and 0.2 ≤ NDVI ≤ 0.5, respectively. The non-vegetation class was then categorized to soil, rock, and man-made classes using land use map. The spectral indices of these classes were then calculated, and the corresponding model trained in the third stage was used to estimate the LSE for that band. The results of LSE estimations were compared with the standard product of each sensor. Due to the lack of standard product for Landsat-8, the ASTER product was used as a substitute. For better analysis, the proposed method was also evaluated with other semi-empirical methods developed for MODIS, ASTER and OLI/TIRS sensors. This evaluation showed that the lowest Root Mean Square Error (RMSE) values for OLI/TIRS bands 10 and 11 are 0.0070 and 0.0075 obtained, respectively, by bagging and RF regression methods. For ASTER bands 13 and 14, the lowest RMSE values of 0.0078 and 0.0077 are both obtained by RF regression. For MODIS bands 31 and 32, the lowest RMSE values are 0.0053 and 0.0049 and obtained by boosting method. A comparison between the proposed method and other semi-empirical methods provided for these sensors demonstrated the ability of the method to improve the RMSE by up to 0.5%. Regarding the higher accuracy and applicability of the proposed method, it can serve as an effective and efficient means of estimating LSE using remote sensing data.

Broadband reflectance, emittance spectroscopy and self-potential geophysical survey for targeting gold sulphide lode deposit in Bhukia, Rajasthan, India

In this study, we have analyzed the comparative potential of reflectance and emittance bands of advanced spaceborne thermal emission and reflection radiometer (ASTER) sensor for detecting surface exposures of Proterozoic rocks and gossan capping of gold mineralization. In this regard, few new image analysis products are derived. These are matched filtering factor-modified ratio (MFR) image and the inverse of a difference image of the ratio and matched filtering map (IDRM). These image products are used with the conventional ratio images, relative band depth images and index-based principal component (PC) images of reflectance and emittance bands of ASTER for delineating metasediments of the study area. We have found that reflectance band products are superior for mapping metasediments and gossan capping than the emissivity products, which are only suitable to enhance quartzite. Self-potential (SP) geophysical survey is carried out around the identified gossan site as SP is sensitive to sulphide mineralization. Results of the SP survey indicated presence of sulphide enrichment underneath the gossan.

Review of the Role of Remote Sensing Applications in Mineral Exploration and Sustainable Development in Oman

Applications of remotely sensed satellite data are wide and unique in the mapping of different lithologies, mineral resources, and ore deposits. Satellite images are capable in discriminating rock types useful for geological applications and significantly used in the identification of mineral resources. The techniques are low-cost and save time in mapping and exploration of such resources and are well-suitable and applicable to the arid region. Oman has the potential occurrence of the industrial minerals and ore deposits which mostly occur in inaccessible mountains and desert regions where it is difficult to do conventional geological mapping. Thus, understanding the capability of the techniques to map and ex­plore such potential resources by geologists is highly important. The absorption characters of spectral bands of Advanced Spaceborne Thermal Emission and Re­flection Radiometer (ASTER) and selected imaging processing methods namely decorrelation stretching, band ratios, linear spectral unmixing (LSU), and Mixture Tuned Matched Filtering (MTMF) demonstrates the sensor capability of ASTER to map several mineral deposits and different rock lithologies in Oman, which in­cludes limestone, marl, listwaenites, carbonatites, metamorphic zones, caves, karst, springs, vegetation’s, rock fall and slide, Moho, copper, chromite, awaruite, manganese, and gold deposit in different parts of the Sultanate of Oman. It demonstrates the spectral sensitivity of such rocks for simple interpretation over satellite data and describes and distinguishes them based on the absorptions of hydrous minerals in the spectral bands of ASTER for mapping and exploration studies.