Relative Band Depth Research Articles

Exploiting the potential of images from the aster and landsat 9 satellites for the mapping of hydrothermal alteration minerals associated with mineralization in the departments of Abtouyour and Guera, located in the Chadian massif central (republic of Cha

This article deals with the use of remote sensing with Aster and Landsat 9 imagery for mapping hydrothermal alteration minerals and oxides in relation to mineralization. Aster VNIR (Visible and Near Infrared) and SWIR (Mean Infrared) data are used to calculate PCA (Principal Component Analysis), RBD (Relative Band Depth) and BR (Band Ratio). These different parameters are used to highlight the groups of hydrothermal alteration minerals and oxides. Landsat data are used for mapping lithological units using PCA and BR. The identified mining areas coincide with the gold planning sites of Toumka and Lellé and allow to know the interesting areas for future mining prospecting campaigns in the departments of Abtouyour and Guéra (Guéra province).

Integrating remote sensing and geophysical data for mapping potential gold mineralization localities at Abu Marawat area, central Eastern Desert, Egypt

Abu Marawat area in the Central Eastern Desert of Egypt is a very promising mineralization district located in the Golden Triangle area. The current study provides an integrated approach from multisource datasets including; remote sensing, airborne geophysical spectrometry and magnetic data supported by field studies and spectroscopic analyses for delineating potential mineralization localities. Several remote sensing techniques were adopted including; Band Ratios, Relative Band Depth, Mineralogical Indices, Spectral Angle Mapper, and Constrained Energy Minimization. These techniques showed that the alteration mineral assemblage is mainly, kaolinite, sericite, and iron oxides, with less abundant chlorite, epidote, and carbonates. In addition, the radiometry data were processed to map the localities with the highest possibility of potassic alteration abundance by integrating the potassium distribution, K/eTh ratio, and the F-parameter maps. The surface and subsurface linear structural features were also mapped using Digital Elevation Model (DEM) and aeromagnetic data, respectively. The surface linear structures were found exhibiting E-W and NE-SW trends, while, the subsurface structures showed dominant NW–SE trend. All the depicted fault trends match well with the local and regional geological and tectonic setting of the study area suggesting structural control on the mineralization in this area. Integration between the results obtained from both the remote sensing and the geophysical data was conducted by a GIS weighted overlay model. The obtained mineralization potentiality map highlights eight potential localities for mineralization. The accuracy of the adopted methodology was demonstrated through fieldwork and spectral analyses; several alteration indicators were observed, including quartz veins, iron oxides, kaolinite, malachite, montmorillonite, chlorite, talc, and sericite alteration indicator minerals. The adopted remote sensing-geophysical approach showed being very effective for mapping the hydrothermal gold-related alteration zones, and is recommended for other similar investigations.

Potentials of spaceborne imaging spectrometer PRISMA, ASTER, and ALOS-1 PALSAR datasets for mineral mapping and geological controls of mineral deposit in Jahazpur, Rajasthan, India

Palaeoproterozoic rocks of the Jahazpur region are well known for talc mineralization and its mining. The present study attempts to identify and map the talc and associated minerals and their structural control using multi-source remote sensing datasets. Remote Sensing studies were carried out using the relative band depth methods for the ASTER dataset for mapping talc and other associated minerals of the region. Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Minimum Noise Fraction (MNF) were applied to the PRISMA dataset to map the lithology of the region. Along with that, the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) algorithms map the talc and clay minerals using the PRISMA dataset. ALOS – 1 PALSAR dataset had been utilized to delineate the various lineaments present in the region at different angles. The obtained mineral maps form the ASTER had been validated with results of the PRISMA classified map and showed a good number of similarities. The obtained results from remote sensing have been further validated with the help of field survey and XRD analysis which confirms the presence of talc and clay minerals in the region. The structural pattern of the lineament shows the similarity in the direction orientation with the Jahazpur Thrust. Dolomites and clay minerals were mapped around the talc mining region which suggests that the alteration of these minerals played an important role in the formation of talc. Clay minerals were also mapped there and formed due to the weathering of the granites of Berach and Jahazpur present in the region. Both talc and clay deposits are present at the higher lineament density zones which represents the structural control over the mineralization. Therefore, the mineral deposits of the Jahazpur region are mineralogical and structurally controlled.

Effective delineation of rare metal-bearing granites from remote sensing data using machine learning methods: A case study from the Umm Naggat Area, Central Eastern Desert, Egypt

Albitized granite (ABG) is considered as one of the most significant hosts of rare metals (RMs). Consequently, adequate recognition of ABG through proper lithological discrimination highly increases the targeting of rare metal resources. In order to delineate outcrops of ABG from satellite data, our study integrates eight image enhancement techniques, including optimum index factor, false color composites, band rationing, relative band depth, independent component analysis, principal component analysis, decorrelation stretch, minimum noise fraction transform, and spectral indices ratios, for the interpretation of ASTER and Sentinel-2 (S2) datasets. This integrated approach allows the effective discrimination of AGB outcrops in the Umm Naggat area, Central Eastern Desert, Egypt. The interpretation maps derived from these integrated image processing techniques were systematically verified in the field and formed the base for the feature selection process (i.e., training and testing data delineation) of different lithologies supported by the support vector machine algorithm (SVM). In order to produce a high‐quality lithological interpretation map, SVM was applied to Sentinel-2, ASTER, and combined ASTER-S2 datasets. The fused ASTER-S2 classification properly delineates ABG, as verified by our field investigations and confirmed by previous geological maps. Furthermore, comprehensive structural analysis (lineaments extraction and their density map) and hydrothermal alteration detection were performed to check the spatial association between the distribution of ABG, higher density zones, and highly altered areas, that in turn, could shed light on new potentially mineralized zones and proposed exploration targets. Our study reveals new ABG occurrences mainly situated in the southern and southwestern parts of the study area, and it confirms the location of known mineralized zones in the northern part of the Umm Naggat region. The distribution of ABG and its spatial correlation with alteration and high structural density zones suggest that rare‐metal mineralization is mostly structurally controlled (NW, NNW, NNE, and N-S), demonstrating the higher possibility of metasomatic enrichment of rare-metals within the study area. Our study provides an updated geological map of the study area based on the SVM‐supported interpretation of ASTER-S2 data. Importantly, the results reveal a high exploration potential for rare‐metal mineralization at Umm Naggat and defining new anomalies for follow‐up work by geochemical soil surveys.

Integration of multi-sensor remote sensing, geological and geochemical data for delineation of Pb–Zn bearing carbonates of Middle Aravalli group in Zawar–Dungarpur Belt, NW India

The rocks of the Aravalli Protocontinent of NW India are enriched in lead–zinc bearing deposits amongst which the Zawar mineralized belt is one of the famous for base metal deposits and was mined since ancient times. In the present study, an attempt has been made to identify and map the extension of the mineralized belt and base metal prognostic zones using the integration of multi-sensor remote sensing, geological and geochemical data. Remote Sensing studies were carried out using ASTER, AVIRIS-NG, and ASAR datasets to understand the extension and associated structural features of host rocks (dolomite in the present case) of lead–zinc mineralization from the Middle Aravalli Group. Relative band depth (B6 + B9/B8) was used to delineate the dolomite of the region using the ASTER imagery. Mineral map was derived using the AVIRIS-NG dataset with the help of the MTMF algorithm. Multifrequency and multipolarization ASAR datasets demarcated the structural features in the complexly deformed rocks of the extended belt. The obtained results from remote sensing were validated with the help of geological and geochemical studies. Geological studies (field surveys and petrographic studies) confirmed the presence of dolomites and associative mafics. Mineralogical, major oxides and trace elements data further substantiated the presence of dolomite, associated sulfides such as galena, sphalerite, pyrite, and chalcopyrite, and lead, zinc and copper in the Zawar–Dungarpur Belt. Presence of chromium and nickel were observed through the trace element studies of dolomite belt. The trace elements interpolated maps were superimposed by traced structural maps using ASAR datasets. The densely populated E-W lineaments are considered the suitable zones for base metal accumulation. These lineaments carried the base metal bearing fluid along with a low concentration of Chromium and Nickel. Under the finding of this study, the northern head of Hati Magra and near Keekawat are the suitable zones for Pb–Zn sulfide mineralization.

Application of Dirichlet Process and Support Vector Machine Techniques for Mapping Alteration Zones Associated with Porphyry Copper Deposit Using ASTER Remote Sensing Imagery

The application of machine learning (ML) algorithms for processing remote sensing data is momentous, particularly for mapping hydrothermal alteration zones associated with porphyry copper deposits. The unsupervised Dirichlet Process (DP) and the supervised Support Vector Machine (SVM) techniques can be executed for mapping hydrothermal alteration zones associated with porphyry copper deposits. The main objective of this investigation is to practice an algorithm that can accurately model the best training data as input for supervised methods such as SVM. For this purpose, the Zefreh porphyry copper deposit located in the Urumieh-Dokhtar Magmatic Arc (UDMA) of central Iran was selected and used as training data. Initially, using ASTER data, different alteration zones of the Zefreh porphyry copper deposit were detected by Band Ratio, Relative Band Depth (RBD), Linear Spectral Unmixing (LSU), Spectral Feature Fitting (SFF), and Orthogonal Subspace Projection (OSP) techniques. Then, using the DP method, the exact extent of each alteration was determined. Finally, the detected alterations were used as training data to identify similar alteration zones in full scene of ASTER using SVM and Spectral Angle Mapper (SAM) methods. Several high potential zones were identified in the study area. Field surveys and laboratory analysis were used to validate the image processing results. This investigation demonstrates that the application of the SVM algorithm for mapping hydrothermal alteration zones associated with porphyry copper deposits is broadly applicable to ASTER data and can be used for prospectivity mapping in many metallogenic provinces around the world.

Potentials of Airborne Hyperspectral AVIRIS-NG Data in the Exploration of Base Metal Deposit—A Study in the Parts of Bhilwara, Rajasthan

In this study, we have processed the spectral bands of airborne hyperspectral data of Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) data for delineating the surface signatures associated with the base metal mineralization in the Pur-Banera area in the Bhilwara district, Rajasthan, India.The primaryhost rocks of the Cu, Pb, Zn mineralization in the area are Banded Magnetite Quartzite (BMQ), unclassified calcareous silicates, and quartzite. We used ratio images derived from the scale and root mean squares (RMS) error imagesusing the multi-range spectral feature fitting (MRSFF) methodto delineate host rocks from the AVIRIS-NG image. The False Color Composites (FCCs) of different relative band depth images, derived from AVIRIS-NG spectral bands, were also used for delineating few minerals. These minerals areeither associated with the surface alteration resulting from the ore-bearing fluid migration orassociated with the redox-controlled supergene enrichments of the ore deposit.The results show that the AVIRIS-NG image products derived in this study can delineate surface signatures of mineralization in 1:10000 to 1:15000 scales to narrow down the targets for detailed exploration.This study alsoidentified the possible structural control over the knownsurface distribution of alteration and lithocap minerals of base metal mineralizationusing the ground-based residual magnetic anomaly map. This observationstrengthens the importance of the identified surface proxiesas an indicator of mineralization. X-ray fluorescence analysis of samples collectedfromselected locations within the study area confirms the Cu-Pb-Zn enrichment. The sulfide minerals were also identified in the microphotographs of polished sections of rock samples collected from the places where surface proxies of mineralization were observed in the field. This study justified the investigation to utilize surface signatures of mineralization identified using AVIRIS-NG dataand validated using field observations, geophysical, geochemical, and petrographical data.

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.

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.

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.

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.

Bloodstain detection and discrimination impacted by spectral shift when using an interference filter-based visible and near-infrared multispectral crime scene imaging system

Bloodstain detection and discrimination from nonblood substances on various substrates are critical in forensic science as bloodstains are a critical source for confirmatory DNA tests. Conventional bloodstain detection methods often involve time-consuming sample preparation, a chance of harm to investigators, the possibility of destruction of blood samples, and acquisition of too little data at crime scenes either in the field or in the laboratory. An imaging method has the advantages of being nondestructive, noncontact, real-time, and covering a large field-of-view. The abundant spectral information provided by multispectral imaging makes it a potential presumptive bloodstain detection and discrimination method. This article proposes an interference filter (IF) based area scanning three-spectral-band crime scene imaging system used for forensic bloodstain detection and discrimination. The impact of large angle of views on the spectral shift of calibrated IFs is determined, for both detecting and discriminating bloodstains from visually similar substances on multiple substrates. Spectral features in the visible and near-infrared portion employed by the relative band depth method are used. This study shows that 1 ml bloodstain on black felt, gray felt, red felt, white cotton, white polyester, and raw wood can be detected. Bloodstains on the above substrates can be discriminated from cola, coffee, ketchup, orange juice, red wine, and green tea.

APPLICATION OF MULTISPECTRAL SATELLITE DATA FOR GEOLOGICAL MAPPING IN ANTARCTIC ENVIRONMENTS

Abstract. Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica’s geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM), Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Contrast-enhanced Red-Green-Blue (RGB) composites, band ratios and Relative Band Depth (RBD) image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.

Reconstructions of local resource procurement networks at Cerro Baúl, Peru using multispectral ASTER satellite imagery and geospatial modeling

Multispectral remote sensing is increasingly common in archaeology, but is largely oriented towards site-detection applications. A high-resolution approach using ASTER data to map environmental and geological resources in the vicinity of Cerro Baúl is outlined here. Spectral mapping evaluates several band ratio and relative band depth image transforms that target diagnostic reflectance/absorption features of earth materials. Available geological resources had a high degree of spatial heterogeneity, which conditioned household strategies for obtaining raw materials. However, some variability cannot be explained by the geological environment alone. Using Minimum Convex Polygons and Kernel Density home-territory estimates, I outline the spatial organization of resource networks that differed from household to household. Differences in household resource networks suggest that socio-economic factors conditioned the use of materials, including locally-available ones. These results demonstrate the utility of multispectral remote sensing to construct palaeoecological models on a scale congruent with archaeological questions.

Analysis of ASTER data for mapping bauxite rich pockets within high altitude lateritic bauxite, Jharkhand, India

Bauxite deposits of Jharkhand in India are resulted from the lateritization process and therefore are often associated with the laterites. In the present study, ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) image is processed to delineate bauxite rich pockets within the laterites. In this regard, spectral signatures of lateritic bauxite samples are analyzed in the laboratory with reference to the spectral features of gibbsite (main mineral constituent of bauxite) and goethite (main mineral constituent of laterite) in VNIR–SWIR (visible-near infrared and short wave infrared) electromagnetic domain. The analysis of spectral signatures of lateritic bauxite samples helps in understanding the differences in the spectral features of bauxites and laterites. Based on these differences; ASTER data based relative band depth and simple ratio images are derived for spatial mapping of the bauxites developed within the lateritic province. In order to integrate the complementary information of different index image, an index based principal component (IPC) image is derived to incorporate the correlative information of these indices to delineate bauxite rich pockets. The occurrences of bauxite rich pockets derived from density sliced IPC image are further delimited by the topographic controls as it has been observed that the major bauxite occurrences of the area are controlled by slope and altitude. In addition to above, IPC image is draped over the digital elevation model (DEM) to illustrate how bauxite rich pockets are distributed with reference to the topographic variability of the terrain. Bauxite rich pockets delineated in the IPC image are also validated based on the known mine occurrences and existing geological map of the bauxite. It is also conceptually validated based on the spectral similarity of the bauxite pixels delineated in the IPC image with the ASTER convolved laboratory spectra of bauxite samples.

Hydrothermal Alteration Mapping Using ASTER Data for Reconnaissance Porphyry Copper Mineralization in the Ahar Area, NW Iran

The Ahar area is located in East Azarbaijan province, and covers an area of about 2,500 km2. Spectral mapping techniques were applied on VNIR and SWIR of ASTER data for discriminating between hydrothermal alteration zones and the identification of high potential mineralized lithological unit associated with hydrothermal porphyry copper mineralization in the Ahar. In this research to remove atmospheric and topographic effects from ASTER data, the log-residual method (LRM) was used. Four methods, Relative Band Depth Ratios (RBD), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and matched filtering (MF), were used to processing and interpretation of remote sensing data in the study area. Results show that ASTER images provide preliminary mineralogy information and geo-referenced alteration maps at low cost and with high accuracy for reconnaissance porphyry copper mineralizations.

Lithological discrimination of the Phenaimata felsic–mafic complex, Gujarat, India, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

This study deals with an evaluation of the efficacy of an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image for lithological mapping. ASTER level-1B data in the visible near-infrared (VNIR), short wave infrared (SWIR) and thermal infrared (TIR) regions have been processed to generate a lithological map of the study area in and around the Phenaimata igneous complex, in mainland Gujarat, India. ASTER band combinations, band ratio images and spectral angle mapper (SAM) processing techniques were evaluated for mapping various lithologies. The reflectance and emissivity spectra of rock samples collected from the study area were obtained in the laboratory and were used as reference spectra for ASTER image analysis. The original data in the scaled digital number (DN) values were converted to radiance and then to relative reflectance by using a scene-derived correction technique prior to SAM classification. The SAM classification in the VNIR–SWIR region is found to be effective in differentiating felsic and mafic lithologies. The relative band depth (RBD) images were generated from the continuum-removed images of ASTER VNIR–SWIR bands. Four RBD combinations (3, 5, 6 and 8) were used to identify Al-OH (aluminium hydroxide), Fe-OH (iron hydroxide), Mg-OH (magnesium hydroxide) and CO3 (carbonate) absorption from various lithological components. ASTER TIR spectral emittance data and the laboratory emissivity measurements show the presence of a number of discrete Si-O spectral features that can differentiate mafic and felsic rock types reflecting the lithological diversity around the regions of Phenaimata igneous complex. SAM classification using emittance data failed to distinguish the felsic and mafic lithology due to the wider spectral bandwidth. The felsic class comprises the granitoid composition of rocks. RBD12 and 13 images in the TIR region were used to derive the mafic index (MI) and the silica index (SI). The MI shows the highest value in regions of gabbro–basalt occurrence, while the SI indicates regions of high silica content. The MI is lowest in regions where granophyres occur. The complimentary attributes based on the spectral reflectance and emittance data resulted in the discrimination of silica-rich and silica-poor lithologies.

Remote sensing of Carhuarazo volcanic complex using ASTER imagery in Southern Peru to detect alteration zones and volcanic structures – a combined approach of image processing in ENVI and ArcGIS/ArcScene

A combined approach to detect hydrothermal alteration zones and their mineral distribution is proposed for a relatively remote area around the Carhuarazo volcanic complex in southern Peru encompassing 2222 km2. In this region, tertiary volcanic structures associated with hydrothermal alteration are well known to host epithermal ore deposits. We make an attempt to detect and to quantify alteration minerals based on spectral analysis using ASTER reflectance data product provided by LP-DAAC. Besides commonly used ratio images, mineral indices (MI) and relative band depth images (RBD), we also extracted endmember spectra using Pixel-Purity-Processing preceded by minimum noise fraction transformation. These spectra are thought to represent the spectrally purest pixel of the image and show the typical absorption features of the main constituents. Based on this assumption, we used different spectral analysis methods in order to extract the most important alteration minerals for such an environment. These minerals were then used for matched filter processing in areas showing high values in MIs and RBDs. Using this method, we detected and mapped argillic alteration and variations in the distribution of important minerals like alunite, kaolinite or nacrite. There were no indications for the presence of propilitization at ASTER spatial resolutions. Our method can be applied easily to any ASTER scene and provides information about the intensity of alteration and the character of alteration zones. The intensity is highest in the centre of the Carhuarazo volcanic complex and is mostly argillic with a high content of alunite, dickite and other clay minerals.

Spectral imaging of martian water ice clouds and their diurnal behavior during the 1999 aphelion season ( Ls = 130°)

We report high-spectral-resolution (λ/δλ = 800–2300) near-infrared mapping observations of Mars at L s = 130° (April 1999), which were obtained by drift-scanning the cryogenic long-slit spectrometer at the KPNO 2.2-m telescope across the disk. Data were reformatted into calibrated spectral image cubes ( x,y,λ) spanning 2.19 to 4.12 μm, which distinguish atmospheric CO 2 features, solar lines, and surface and aerosol features. Maps of relative band depth between 3.0 and 3.5 μm trace water ice clouds and show the diurnal evolution of features in the persistent northern summer aphelion cloud belt, which was mapped contemporaneously but at fixed local time by the Mars Global Surveyor Thermal Emission Spectrometer (MGS/TES). Cloud optical depth, particle sizes, and ice aerosol content were estimated using a two-stream, single-layer scattering model, with Mie coefficients derived from recently published ice optical constants, followed by a linear spectral deconvolution process. A comparison of data and model spectra shows evaporating nighttime clouds in the morning followed by afternoon growth of a prominent orographic cloud feature on the west flank of Elysium Mons. Cloud optical depth at 3.2 μm evolved to 0.28 ± 0.13 and ice aerosol column abundance to 0.9 ± 0.3 pr μm in the afternoon. Column abundances as large as 0.17 pr μm were retrieved in nonorographic clouds within the aphelion cloud band around midday. These clouds exhibit a modest decline in optical depth during the afternoon. Results show that ice particle radii from <2 μm to >4 μm exist in both cloud types. However, large particles dominate the spectra, consistent with recent MGS/TES emission phase function measurements of aphelion cloud aerosol properties.