Spectral Feature Fitting Research Articles

Lithological discrimination using ASTER and Hyperion data in Salem District, Tamil Nadu

— Lithological mapping is a crucial factor in identifying and mapping the spatial distribution of minerals. It aids in accurately defining the most promising primary prospects for local exploration. The differentiation of rock units across a wider region is likely to be attributed to remotely sensed satellite data. Therefore, the research focuses on utilizing remote sensing methods to create a geological map for a specific area in Salem district, Tamil Nadu, by employing HYPERION and ASTER satellite images. Various techniques, such as Band Ratio (BR), Spectral Angle Mapper (SAM), Minimum Noise Fraction (MNF), Mixture Tuned Mapped Filtering (MTMF), Spectral Feature Fitting (SFF), and Support Vector Machines (SVMs), are utilized to classify lithological units, which are crucial for data analysis. The outcomes of these methods will be compared to field-mapped geological boundaries to assess accuracy. In the final phase, a highly precise geological map is produced by combining remote sensing data with on-site investigations. The application of these approaches holds significant potential for enhancing geological mapping and mineral exploration in hard-to-reach areas.

Using the band ratio approach, FULL-PIXEL (SAM and SFF) and SUB-PIXEL (MF and SID) methodologies to discover areas with alteration using the Aster sensor: a case study in north westen Iran - Sivardaghi Area

ASTER sensor data is among the most potent satellite data accessible for doing geological investigations, with images for the whole earth's surface. In order to test the capability of this sensor to detect places with geochemical alterations, photographs of Mount Seiver Daghi in the western Iranian province of Samal were utilized in this study. This region, which comprises of magmatic and volcanic terrain, is part of the Arsbaran territory and is covered by intrusive masses with alluvial and sedimentary deposits. To conduct this study, an ASTER measuring frame was utilized, which, after performing atmospheric corrections using the internal average relative reflectance (IARR) method of false color composite images and principal component analysis (PCA), was able to differentiate between different lithological units using the Band assignment method, full-pixel methods of spectral angle mapper (SAM) and base spectrum algorithm of spectral feature fitting (SFF) as well as sub-pixel methods of matched filtering. The study demonstrates that the approach of principal component analysis and false color composition is efficient for distinguishing sedimentary rock units from igneous rock units, and its application is suggested for the designated rock units. Due to the lack of spectral characteristics of feldspars and quartz in the short infrared wavelength range, the basic spectrum methods utilized in this work are incapable of identifying such minerals. It is not advised to use these algorithms to distinguish between various magmatic units.

Determination of alteration zones applying fractal modeling and Spectral Feature Fitting (SFF) method in Saryazd porphyry copper system, central Iran

The target of this research is recognition of the alteration zones utilizing concentration-area fractal methodology according to the reflection of the main minerals of each alteration zone that enhanced by Spectral Feature Fitting (SFF) method due to Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) satellite images in Saryazd porphyry system, central Iran. The alterations and mineralization developed in Eocene volcanics. Remote sensing results achieved by the SFF method and Concentration -Area (C - A) fractal modeling represent different parts of propylitic, argillic and phyllic alteration zones due to their intensity and pixel values. In addition, the results reveal that there is a ring-shaped structure in the alteration zones, which are correlated with results, derived from X-Ray Diffraction (XRD) analyses and field observations.

The synergistic use of multi-scale remote sensing data for the identification of hydrothermal alteration patterns in Los Frailes, Spain

• FieldSpec4, SisuROCK, AisaFenix and WorldView-3 results are used synergistically. • Spectral data characterise hydrothermal alterations typical for massive sulphides. • Chlorite and white mica mapping results coincide mostly between the data scales. • Mapping discrepancies are explained by different data types and analysis methods. • Multi-scale spectral data can help to identify potential exploration targets. Remote sensing data can be successfully applied in mineral resource prospecting and exploration. With the increasing number of remote sensing sensors and methods, the application of multi-scale remote sensing data has met a broad audience in the geological remote sensing community over the last few years. Multi-scale remote sensing data close the scale gap between distal (satellite) and proximal (laboratory) remote sensing data, offering both a general and detailed overview of the target and allowing a synergistic use. In this study, the volcano-sedimentary hosted massive sulphide ore deposit Los Frailes in the east of the Iberian Pyrite Belt (IPB) in Spain is investigated for the first time with multi-scale remote sensing techniques. A typical hydrothermal alteration zonation is associated to the massive sulphide ore body in Los Frailes, which is characterised by an inner chlorite-rich zonation showing a strong Fe-enrichment and a peripheral muscovite-rich zonation, which is moderately enriched in Fe. The characterisation of these zones support traditional mineral exploration techniques especially in the prospecting phase by detecting regions of interest, thereby reducing time and cost consumption. By evaluating the synergistic use of multi-scale remote sensing data for massive sulphide exploration, an enhanced application for the economic prospecting and exploration of mineral resources in Los Frailes is introduced. Optical data are used for the detection, identification and characterisation of chlorite and white mica occurrences and compositions. A drill core is analysed with the FieldSpec4 Hi-res hyperspectral point spectrometer. Rock samples are investigated in the laboratory using the SisuROCK hyperspectral core imaging station. AisaFENIX hyperspectral field-based and WorldView-3 multispectral satellite data of the open pit are analysed. The mineral(-group) identification and characterisation are performed with either spectral feature fitting methods (hyperspectral) or mineral indices (multispectral). Hyperspectral analyses show Mg-/Al-substitutions due to Fe-enrichment owing to wavelength shifts of the absorption maximum in chlorite and white mica, respectively. The identification and characterisation of the Fe-OH absorption feature of chlorite at around 2250 nm is more challenging compared to the Al-OH absorption feature of muscovite at around 2200 nm because the spectral signature is more subtle regarding the depth and width. However, the chloritic hydrothermal alteration zonation in the footwall is successfully detected in all scales. The hydrothermal muscovite-rich zonation in the footwall is barely outcropping in the pit and is not captured in the drill core. However, the muscovite-rich alteration zonation in the hanging wall is indicated in all scales. Discrepancies in the results arise mainly from different spectral and spatial resolutions of the sensors and differing data acquirement conditions, such as different surface exposures, viewing angles and illumination conditions. The results show that the multi-scale method offers great opportunities to localise potential prospecting and exploration targets in the Iberian Pyrite Belt. The synergistic use of the different remote sensing scales offers a complete picture of the target by gaining macroscopic to regional spectral information collectively, which is superior to using only one scale. The method is relatively fast and cost-effective, which makes the identification of potential exploration targets more efficient.

Soil clay minerals abundance mapping using AVIRIS-NG data

Advanced hyperspectral remote sensing technology can identify various clay minerals in the soil. The improved spectral and spatial resolution of the airborne hyperspectral sensor can be used for a better interpretation of clay mineral abundance in the soil. This research utilizes the high-resolution image data acquired from Advanced Visible Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) on an airborne platform to map the abundance of clay minerals in the Udaipur region of Rajasthan (24° 34′ 16.5720′' N, 73° 41′ 29.5584′' E). The representative soil samples for various soil clay minerals, e.g., kaolinite, montmorillonite, and illite, were classified from AVIRIS-NG data using a spectral feature fitting algorithm. A total of thirty sites were selected from agricultural and wastelands for soil sample collection. X-ray diffraction (XRD) analysis of representative soil samples was carried out to find the percentage and type of clay minerals present. Regression analysis between absorption peak depth values estimated from the hyperspectral image of the sampling sites in the spectral region from 2205 to 2214 nm and corresponding clay content value showed a significant relationship. The regression line obtained for the known pixels was used to prepare the mineral abundance map over the study area. This study significantly indicates the dominance of montmorillonite clay mineral over kaolinite and illite in the soils of the Udaipur region.

Exploring beach placer minerals in the east coast of Tamil Nadu, India, using EO-1 Hyperion data

Recent advancements in remote sensing facilitate the mapping of mineral occurrences but lack quantitative estimation of mineral abundances. In the present study, EO-1 Hyperion data are used for mapping and estimating beach placer minerals in the Cuddalore coastal stretch of Tamil Nadu, India, using spectral angle mapper (SAM) algorithm, continuum removed band depth analysis, and random forest (RF) regression. Strategic beach placer minerals are exposed in the image due to their specific spectral reflection/absorption characteristics; these unique settings are used to explore their spatial distribution from associated features. EO-1 Hyperion images are analyzed for (i) atmospheric correction; (ii) selection and transformation of optimum bands; (iii) fixing the input pixels from selected bands; (iv) generating n-D angle—for the preparation of end-members with unique spectra of mineral classes; (v) comparative analysis between true end-member and reference spectra of minerals using SAM, spectral feature fitting, and binary encoding algorithms; and (vi) image classification using SAM. The result of SAM shows the occurrence of placer mineral deposits such as zircon with an overall accuracy of 81.06% and Kappa coefficient of 0.71. The zircon shows strong absorption in spectral geometric parameters of EO-1 Hyperion data, such as band depth and band area at the spectral range of 1075 to 1150 nm. The positive correlation between geometric parameters of mineral spectra in its absorption characteristics and the mineral concentration of in situ samplings is used for developing an RF prediction model for estimating the placer minerals from beach sand deposits. Significantly, the lower RMSE values estimated at 0.082 and 0.156 for reference spectra (in situ) and image spectra respectively proved the ability of EO-1 Hyperion data for quantifying mineral resources.

Integrating remote sensing data, GIS analysis and field studies for mapping alteration zones at Wadi Saqia area, central Eastern Desert, Egypt

Remote sensing data, spectral analyses, Geographic Information System (GIS) tools and field work were integrated for detecting the spatial distribution of the alteration zones in the study area. Remote sensing studies including; spectral signatures analyses and satellite image processing, were used for identifying the alteration minerals setting of the study area then extracting the alteration zones. A field study was carried out to the study area and several tens of samples were collected. The spectral behavior of the collected samples was obtained using the “Advanced Spectral Devices (ASD) TerraSpec Halo mineral identifier” handheld spectro-radiometer. Spectral analyses were carried out on signatures of selected samples to obtain the characterizing absorption features and to reveal the identity of the alteration minerals (end-members) representing the alteration zones in the area. The identified end-members included; Clay minerals, white Mica, Epidote and Iron oxides. Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), Constrained Energy Minimization (CEM), and Mixture Tuned Matched Filtering (MTMF) alteration mapping techniques were used to map the abundance of the identified alteration minerals from ASTER satellite image data. Lineaments were extracted automatically using combined hill-shade images obtained at multi-azimuths derived from Allos PALSAR 12.5 m Digital Elevation Model (DEM) data. The alteration and lineament data were integrated together using the GIS “Weighted Overlay Analysis” tool to delineate the most potential areas for alteration zones existence. The results were validated through plotting the field observation points on the resulted final alteration map; the accuracy was estimated by about 80%.

Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2 Imagery of Karimunjawa and Kemujan Island, Central Java Province, Indonesia

Mangrove mapping at the species level enables the creation of a detailed inventory of mangrove forest biodiversity and supports coastal ecosystem management. The Karimunjawa National Park in Central Java Province is one of Indonesia’s mangrove habitats with high biodiversity, namely, 44 species representing 25 true mangroves and 19 mangrove associates. This study aims to (1) classify and group mangrove species by their spectral reflectance characteristics, (2) map mangrove species by applying their spectral reflectance to WorldView-2 satellite imagery with the spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF) algorithms, and (3) assess the accuracy of the produced mangrove species mapping of the Karimunjawa and Kemujan Islands. The collected field data included (1) mangrove species identification, (2) coordinate locations of targeted mangrove species, and (3) the spectral reflectance of mangrove species measured with a field spectrometer. Dendrogram analysis was conducted with the Ward linkage method to classify mangrove species based on the distance between the closest clusters of spectral reflectance patterns. The dendrogram showed that the 24 mangrove species found in the field could be grouped into four levels. They consisted of two, four, and five species groups for Levels 1 to 3, respectively, and individual species for Level 4. The mapping results indicated that the SID algorithm had the highest overall accuracy (OA) at 49.72%, 22.60%, and 15.20% for Levels 1 to 3, respectively, while SFF produced the most accurate results for individual species mapping (Level 4) with an OA of 5.08%. The results suggest that the greater the number of classes to be mapped, the lower the mapping accuracy. The results can be used to model the spatial distribution of mangrove species or the composition of mangrove forests and update databases related to coastal management.

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.

Integration of concentration-area fractal model and relative absorption band depth method for mapping hydrothermal alterations using ASTER data

Those image processing methods which use both spatial and spectral properties of remotely sensed images often increase accuracy of image classification. In this study, the concentration-area (C-A) fractal model and Relative absorption Band Depth (RBD) were applied to map hydrothermal alteration zones using ASTER data covering the northern part of Rabor area, Iran. Based on the field observations and spectral analysis of rock samples, three types of RBD were calculated and applied to map hydrothermal altered rocks (RBD6 for phyllic, RBD8 for propylitic, and RBD5 for argillic). A log-log plot of area-digital number value for RBD images showed that there are three populations in each image. Representation of these populations revealed that the third population of each RBD has enhanced separation of alteration zones. To verify the results, a spectral library of ground rock samples was built and used to compare with 10 spectra derived from each image. Spectral Angle Mapping, Spectral Feature Fitting, and Binary Encoding were applied to assess the matching of image spectra with the spectral library spectra. Results confirmed that third population of RBD6 and RBD8 contain pure pixels of phyllic and propylitic alterations, respectively whereas there are some interference between argillic and phyllic alterations in RBD5.

Exploring the Mineralogy at Lonar Crater with Hyperspectral Remote Sensing

Abstract The earth crust is made up of variety of minerals. These minerals are having very significant applications in our day today life. The various studies, characterizing physical, chemical, electrical, structural properties, have been carried out on the Lonar crater for studying mineralogy, surface morphology and geology but has not been done by remote sensing technology. So, the proposed work focused on exploring the mineralogy at the Lonar crater by using high resolution hyperspectral imageries. The spectral reflectance of minerals was characterized by using FieldSpec4 spectroradiometer. The minerals at Lonar crater were explored by performing preprocessing and spectral analysis. The techniques used in the work are Spectral Angle Mapper and Spectral Feature Fitting. The results of the work marked the presence of pigeonite and augite at Lonar crater which indicates that this crater is the result of extrusive volcanic activity. Also, the presence of augite underneath basaltic igneous rocks as the rock type of Lonar crater. The salinity of the Lonar lake is proved by the presence of mirabilite and salt. Thus, the important results of this work are presence of minerals quartz, actinol, jarosite, pigeonite, augite, albite, mirabilite and scolecite. The significance of these minerals related to the crater is discussed here. It also validated the existence of these minerals which were identified through the previous geological, chemical, physical, electrical and magnetic studies and the minerals pyrite, chlorite, richter, illite, limonite, allanite, amphibolite and margarite were also identified.

Using geochemical imaging data to map nickel sulfide deposits in Daxinganling, China

Nickel sulfide deposits occur in ultramafic rocks in the Daxinganling area, China; however, the prospectivity of these deposits has received little attention. This study transformed rasterized regional 1:200,000 geochemical data into spectral-like data and then used hyperspectral tools of the spectral angle mapper (SAM) to classify possible ultramafic lithologies and the multirange spectral feature fitting (MRSFF) method to classify prospective areas that are similar to a typical Gaxian Ni deposit. The prospective area map generated by the MRSFF implies the possible occurrence of ultramafic rocks classified by the SAM method. These results confirm the suitability of this innovative approach for prospectivity mapping of Ni sulfide deposits.

Characterization and mapping of hematite ore mineral classes using hyperspectral remote sensing technique: a case study from Bailadila iron ore mining region

The study demonstrates a methodology for mapping various hematite ore classes based on their reflectance and absorption spectra, using Hyperion satellite imagery. Substantial validation is carried out, using the spectral feature fitting technique, with the field spectra measured over the Bailadila hill range in Chhattisgarh State in India. The results of the study showed a good correlation between the concentration of iron oxide with the depth of the near-infrared absorption feature (R2 = 0.843) and the width of the near-infrared absorption feature (R2 = 0.812) through different empirical models, with a root-mean-square error (RMSE) between < 0.317 and < 0.409. The overall accuracy of the study is 88.2% with a Kappa coefficient value of 0.81. Geochemical analysis and X-ray fluorescence (XRF) of field ore samples are performed to ensure different classes of hematite ore minerals. Results showed a high content of Fe > 60 wt% in most of the hematite ore samples, except banded hematite quartzite (BHQ) (< 47 wt%).

Spectral and Chemical Characterization of Copiapite and Rozenite from Padinjarathara in Wayanad, Southern India: Implications for Mars Exploration

Copiapite (Fe2+Fe3+4(SO4)6(OH)2 ∙ 20 H2O) and rozenite (Fe2+(SO4) ∙ 4H2O) are secondary hydrous sulfate minerals, mostly formed because of oxygenation and weathering events of primary sulfides on Earth. Acidophiles, mainly archaea and bacteria, and specifically anaerobic methanogens (methane-producing microorganisms) have been detected in regions where alteration of primary sulfide phases to secondary sulfates are predominant. These secondary sulfate minerals are significant in defining past geological environments on Earth and other rocky planets such as Mars. We discuss here the results of chemical and spectral analyses of copiapite and rozenite found in massive sulfide zones associated with banded iron formations (BIFs) in the Wayanad region in Kerala, southern India. The results from different spectroscopic techniques — VNIR reflectance, TIR (emitted radiation), FTIR, Laser Raman, and X-ray diffraction — were recorded and matched with existing literatures and databases. Different matching algorithms like Spectral Feature Fitting (SFF), Spectral Similarity Value (SSV), Modified Spectral Angle Similarity (MSAS), and Pearsonian Correlation Coefficient (PCC) were utilized in order to quantitatively match the reflectance spectra with the reference spectra (USGS and RELAB). The genesis of copiapite and rozenite in the area is through seasonal and temporary development of an acidic environment, with the high elevations of the Wayanad plateau providing the necessary low-humidity condition during the dry season. Copiapite and rozenite were detected as alteration products in different regions on Mars, which can provide insights into environmental conditions that prevailed during the biogeochemical evolution of Mars. The study of copiapite and rozenite formation in a terrestrial environment will therefore enhance our understanding of similar mineral precipitation, genesis, and fluvial processes on Mars. Future missions to Mars could also use the data obtained from the present study to calibrate similar instruments to detect these secondary sulfate minerals.

The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder – V. Rotational measurements of NGC 891

ABSTRACT The ESA Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF) project is an automated spectral feature fitting routine developed within the SPIRE instrument team to extract all prominent spectral features from all publicly available SPIRE FTS observations. In this work, we demonstrate the use of the FF information extracted from three observations of the edge-on spiral galaxy NGC 891 to measure the rotation of N ii and C i gas at far-infrared frequencies in complement to radio observations of the [H i] 21-cm line and the CO(1-0) transition as well as optical measurements of Hα. We find that measurements of both N ii and C i gas follow a similar velocity profile to that of H i and Hα showing a correlation between neutral and ionized regions of the interstellar medium in the disc of NGC 891.

Airborne hyperspectral characterisation of hydrothermal alteration in a regolith-dominated terrain, southern Gawler Ranges, South Australia

Key alteration minerals associated with epithermal and porphyry Cu–Au mineralisation have been successfully identified using HyMap airborne hyperspectral imagery in a regolith-dominated terrain in the southern Gawler Ranges, South Australia. Alteration assemblages were mapped using Spectral Feature Fitting, a spectral matching algorithm, identifying the spatial distribution of localised advanced argillic and broader argillic alteration. X-ray diffraction (XRD) analysis was undertaken to independently identify the mineralogy of 57 surface soil and rock samples collected from the study area. This analysis confirmed the presence of key alteration minerals including alunite, pyrophyllite and dickite. The integration of spectral and XRD analytical techniques allowed interpretation of mineralogical patterns across the landscape. This study demonstrates that it is possible to identify surface alteration related to potential mineralisation using airborne hyperspectral imagery and semi-quantitative XRD even in a weathered regolith-dominated terrain. KEY POINTS Advanced argillic and argillic alteration identified through hyperspectral image analysis in a regolith-dominated terrain X-ray diffraction used to validate the presence of advanced argillic alteration minerals alunite, pyrophyllite and dickite in the landscape Relationship of advanced argillic and argillic alteration interpreted in two key landscape features in the context of a porphyry mineral system Demonstrates potential for detection of alteration signatures with airborne hyperspectral imagery in regolith-dominated terrains elsewhere

Spectral characteristics of talc and mineral abundance mapping in the Jahazpur Belt of Rajasthan, India using AVIRIS-NG data

ABSTRACT Spaceborne data with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Short Wave Infrared (SWIR) bands have been used worldwide in discriminating different clay minerals. However, due to wide bandwidth of ASTER sensors, it is difficult to distinguish between pure and impure variety of talc mineral. The present study highlights the efficacy of airborne hyperspectral data Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) for spectral analysis in talc mineral in the Jahazpur Belt of Bhilwara district in Rajasthan, India. Due to its better spectral and spatial resolution, AVIRIS-NG is found to be extremely useful in identifying talc mineral in SWIR region. Talc is characterized by doublet shaped spectral pattern in AVIRIS-NG image with strong absorption dips at 2289.75 nm and 2314.80 nm which could not be picked up in ASTER image. Spectral matching of talc pixels is verified with the field spectra of samples and available spectral library of United States Geological Survey, Jet Propulsion Laboratory, and International Geological Correlation Programme. Variation in reflectance percentage of different talc pixels is attributed to variation in chemical composition of talc. However, a large number of mixed pixels with spectral pattern of both talc and kaolinite minerals have been identified in AVIRIS-NG image which are found to be an impure variety of talc. Whole-pixel to sub-pixel classification techniques with Spectral Angle Mapper, Spectral Feature Fitting, Mixture Tuned Matched Filtering, and Linear Spectral Unmixing (LSU) techniques have been applied for talc abundance mapping in Jahazpur area. LSU is found to be the most useful and accurate technique in classifying spectrally pure to impure variety of talc.

Per-pixel analysis of ASTER data for porphyry copper hydrothermal alteration mapping: A case study of NE Isfahan, Iran

This paper evaluates the efficiency and capability of per-pixel methods comprising spectral feature fitting (SFF), multi range spectral feature fitting (MRSFF), and spectral information divergence (SID) algorithms in mapping alteration minerals using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. The study area is located in the Saveh-Yazd belt, northeastern Isfahan, Iran, which is the central part of the Urumieh–Dokhtar Magmatic Arc (UDMA). Porphyry copper mineralization formed in association with Oligo-Miocene intrusive bodies, are located in this belt. The hydrothermal alteration zones in the study area are manifested by phyllic, argillic, propylitic, and silicic. Mineralogically, these zones are marked by sericite-illite, kaolinite, montmorillonite, chlorite, epidote, and overprint of iron oxide/hydroxides. The pixel purity index (PPI) was used for extraction of image spectra, which were subsequently used as spectral reference. The SFF algorithm could map the Al–OH bearing mineral assemblages as a mixed alteration zone (phyllic-argillic zone), whereas the MRSFF provided an improved discrimination of sericite-illite and kaolinite minerals. The SID algorithm had the best performance for identifying and mapping these alteration minerals, comparing to the SFF and MRSFF. On the other hand, the results showed that SID and MRSFF algorithms were more efficient than SFF in discriminating the propylitic alteration zone. The field surveys, X-ray diffraction, spectral measurements, and microscopic studies confirmed the occurrence of hydrothermally altered minerals containing sericite-illite, kaolinite-dickite, and chlorite– epidote, which corresponded well to the ground criteria. Considering the potential of SID algorithm in discriminating the target minerals, it could be proposed for mineral mapping as part of exploration projects.

The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder – III. Line identification and off-axis spectra

ABSTRACT The European Space Agency Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF) project is an automated spectral feature fitting routine developed within the SPIRE instrument team to extract all prominent spectral features from all publicly available SPIRE FTS observations. We present the extension of the FF to include the off-axis detectors of the FTS in sparsely sampled single-pointing observations, the results of which have been ingested into the catalogue. We also present the results from an automated routine for identifications of the atomic/molecular transitions that correspond to the spectral features extracted by the FF. We use a template of 307 atomic fine structure and molecular lines that are commonly found in SPIRE FTS spectra for the cross-match. The routine makes use of information provided by the line identification to search for low signal-to-noise ratio features that have been excluded or missed by the iterative FF. In total, the atomic/molecular transitions of 178 942 lines are identified (corresponding to 83 per cent of the entire FF catalogue), and an additional 33 840 spectral lines associated with missing features from SPIRE FTS observations are added to the FF catalogue.