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The Postmasburg manganese ore field currently stands as the second largest in the world, featuring a widespread distribution of mining areas. Remote sensing technology possesses distinct advantages in interpreting geological information at a macro level. To further expand the scope of the Postmasburg manganese ore field and identify new target mining areas, we systematically studied the geological alteration information and structural characteristics of the ore field using various remote sensing interpretation methods. Here we show Landset 8 data was utilized to extract linear structural information from the Postmasburg manganese ore field, while ASTER data was employed to identify mineral alteration anomaly information related to iron staining, manganese mineralization, hydroxyl, and carbonate mineralization within the study area. By comparing the extraction results with regional geological survey data, we discovered that structural lines are well-developed in the study area and generally align with the stratigraphic trend. There is a strong correlation between the distribution locations of iron staining and manganese mineralization alterations. Based on the remote sensing interpretation results, we delineated two prospective mineral exploration areas using the analogy extrapolation method. Here we show the linear structure and alteration information interpretation methods employed in remote sensing technology can effectively reflect the distribution of manganese ore in the Postmasburg area. [ABSTRACT FROM AUTHOR]

Mapping alteration zones, a crucial step for mineral exploration, faces challenges in tropical areas. Dense vegetation hides important geological features, recent clay formation hides deeper alterations, and human activities like farming make it more complicated. However, alteration zones are crucial clues for specific ore deposits. We explore two approaches: one based on knowledge and the other on data. The knowledge-driven method involves experienced geologists analyzing GIS layers, including lineaments, drainage patterns, rock types, and topography. They use this data to identify key signs of ore-forming alterations. Translating this expert knowledge into spatial data helps us map alteration zones effectively. While this approach provides good approximations, it lacks direct evidence. The data-driven method involves advanced remote sensing tools like ASTER imagery. High-resolution data allows us to use image processing techniques to extract alteration information. However, conventional techniques face challenges in the tropics due to dense vegetation and human activity. To overcome this, we use machine learning algorithms trained on carefully selected samples. We found that among selected ASTER-derived products of conventional DIP techniques (reflectance, band ratio, PCA, DPCA), directed PCA alone is capable of demarcating alteration for the study area with a total accuracy of 81.41, 83.92, and 84.42% for LR, ANN, and RF, respectively. Besides, we used contextual geological evidence of alteration presence as another validation method. To validate results, we use the knowledge-driven approach again, employing Relative Alteration Indexes. All alteration indicative field and geological knowledge were weighted with the Analytical Hierarchy Process (AHP) and spatially integrated with three probability classes in the GIS platform. This combined strategy reveals that while Random Forest has the highest accuracy, Logistic Regression yields more geologically significant results. The high value of Relative Alteration Indexes representing highly altered zones indicates their successful mapping from both data and knowledge-driven techniques. This study shows the strengths of both approaches in understanding alteration zones in the tropics. By combining expert knowledge with advanced technology, we can pinpoint areas rich in valuable minerals, even in difficult-to-explore places. Our successful test in the South Purulia region suggests similar discoveries are possible in other unknown areas. [ABSTRACT FROM AUTHOR]

Sodium mondodecyl phosphate (SDP) and isopentenol (IPN), both of premive relevance (SDP and IPN), are selected to construct the protocell model in water. The Vesicles, microtubules and asters phases somehow resembling the morphology and structure of modern cells/organelles were obtained in this single system. The formation of these aggregates is attributed to the intermolecular hydrogen bonding and alkyl chain interdigitated structure. The protocell models not only display remarkable freeze–thaw and wet-dry stabilities by simulating the primordial Earth's diurnal temperature differences and ocean tides but also are able to exhibit cell-like behavior of chemical signaling transition. [Display omitted] Simple single-chain amphiphiles (sodium monododecyl phosphate, SDP) and organic small molecules (isopentenol, IPN), both of primitive relevance, are proved to have been the building blocks of protocells on the early Earth. How do SDP-based membrane and coexisting IPN come together in specific ways to produce more complex chemical entities? What kind of cell-like behavior can be endowed with this protocell model? These are important questions in the pre-life chemical origin scenario that have not been answered to date. The phase behavior and formation mechanism of the aggregates for SDP/IPN/H 2 O ternary system were characterized and studied by different electron microscopy, fluorescent probe technology, DLS, IR, ESI-MS, SAXS, etc. The stability (freeze–thaw and wet-dry treatments) and cell-like behavior (chemical signaling communication) were tested via simulating particular scenarios. Vesicles, microtubules and asters phases resembling the morphology and structure of modern cells/organelles were obtained. The intermolecular hydrogen bonding is the main driving force for the emergence of the aggregates. The protocell models not only display remarkable stabilities by simulating the primordial Earth's diurnal temperature differences and ocean tides but also are able to exhibit cell-like behavior of chemical signaling transition. [ABSTRACT FROM AUTHOR]

The present work enhances mineral exploration in Egypt's Eastern Desert by mapping lithological units and identifying hydrothermal alteration zones, potentially leading to the discovery of economically viable mineral deposits. This study employs a comprehensive approach of integrating multispectral bands from Landsat-9 and ASTER images with airborne radiometric data. Various image enhancement techniques such as False Color Composite (FCC), Minimum Noise Fraction (MNF), and Principal Component Analysis (PCA) are utilized to map enhanced lithological units. Additionally, image classification techniques, including Spectral Angle Mapper (SAM) and Crosta Principal Component (CROSTA PC), are applied to emphasize hydrothermal alteration minerals like alunite, calcite, hematite, illite, chlorite, epidote, kaolinite, montmorillonite, and sericite. Furthermore, radioelement ratios (eU/eTh, eU/K, eTh/K, and eU-(eTh/3.5)) and the F-parameter (K*(eU/eTh)) are utilized. Mineral percentages are determined using Scanning Electron Microscope (SEM), allowing for the observation of ore minerals from the Elkharaza-Dara area deposits, which exhibit varying compositions. Maximum values are recorded for specific elements: aluminum (10.48 wt% Al), silicon (65.38 wt% Si), silver (0.32 wt% Ag), copper (2.65 wt% Cu), gold (5.25 wt% Au), potassium (4.32 wt% K), hafnium (3.84 wt% Hf), calcium (26.94 wt% Ca), carbon (56.92 wt% C), and oxygen (53.71 wt% O). These findings offer valuable insights into the elemental composition of the mineralized deposits in the study area. The multi-algorithm integration approach has been confirmed through various methods, including comparison with existing geological maps, fieldwork, and microscopic analysis of selected samples from alteration zones across the study area. [ABSTRACT FROM AUTHOR]

Alteration minerals and silicification are typically associated with a variety of ore mineralizations and could be detected using multispectral remote sensing sensors as indicators for mineral exploration. In this investigation, the Visible Near-Infra-Red (VNIR), Short-Wave Infra-Red (SWIR), and Thermal Infra-Red (TIR) bands of the ASTER satellite sensor derived layers were fused to detect alteration minerals and silicification in east the Kerdous inlier for cupriferous mineralization exploration. Several image processing techniques were executed in the present investigation, namely, Band Ratio (BR), Selective Principal Component Analysis (SPCA) and Constrained Energy Minimization (CEM) techniques. Initially, the BR and SPCA processing results revealed several alteration zones, including argillic, phyllic, dolomitization and silicification as well as iron oxides and hydroxides. Then, these zones were mapped at sub-pixel level using the CEM technique. Pyrophyllite, kaolinite, dolomite, illite, muscovite, montmorillonite, topaz and hematite were revealed displaying a significant distribution in relation with the eastern Amlen region lithological units and previously detected mineral potential zones using HyMap imaging spectroscopy. Mainly, a close spatial association between iron oxides and hydroxide minerals, argillic, and phyllic alteration was detected, as well as a strong silicification was detected around doleritic dykes unit in Jbel Lkest area. A weighted overlay approach was used in the integration of hydrothermal alteration minerals and silicification, which allowed the elaboration of a new mineral alteration map of study area with five alteration intensities. ASTER and the various employed processing techniques allowed a practical and cost effective mapping of alteration features, which corroborates well with field survey and X-ray diffraction analysis. Therefore, ASTER data and the employed processing techniques offers a practical approach for mineral prospection in comparable settings. [ABSTRACT FROM AUTHOR]

Porphyry deposits are typically associated with specific hydrothermal alteration zones. The identification of hydrothermal alteration patterns in porphyry deposits using remote sensing imagery is a cost-effective tool to identify zones of high potential zones. The West Zafarghand porphyry is located in the northeast of Isfahan, central part of the Cenozoic Urumieh-Dokhtar magmatic arc. Lack of interpretation of the spatial pattern of hydrothermal alteration zones and their relationships to ore mineralisation in the study area has led us to use ASTER remote sensing data to detect alteration patterns. Delineating the extent of hydrothermal alteration zones and high-grade mineralised lithological units is a particular goal of this study. We used various image processing techniques such as False Color Composite, Band Ratio, Principal Component Analysis, Minimum Noise Fraction and Spectral Angle Mapper. Remote sensing results, field observations, petrographic surveys and XRD revealed argillic, phyllic and propylitic hydrothermal alteration zones in the central part of the study area. An overall accuracy of 90% and a kappa coefficient of 0.84 were achieved in this analysis. The spatial distribution of the NE-SW trending phyllic alteration zone discovered in this study could be considered an area of high potential for a comprehensive exploration campaign at this deposit. [ABSTRACT FROM AUTHOR]

In this study, image processing has been applied to ASTER and Sentinel-2A satellite images, and obtained data is used to reveal Fe-bearing rocks in the vicinity of Hasançelebi (Malatya), close to Divriği (Sivas) which is one of the most important iron provenances in the Central-Eastern Anatolia region of Türkiye. Remote sensing images, particularly the visible-near-infrared (VNIR) and partially shortwave infrared (SWIR) bands, have been employed to identify Fe-bearing minerals and rocks. With the purpose of identifying Fe-bearing minerals and rocks, various band rationing processes have been applied. Supervised classification which utilizes a parallelepiped algorithm has been employed on the resulting ratio images to create classification distributions for Fe-bearing minerals. According to the classification results; ferrous iron (Fe2+) and ferric oxides are more associated with ophiolitic rocks, ferrous silicates and ferric iron (Fe3+). The distributions are generally associated with clastic lithologies, and laterite and gossan appear to be associated with volcanic and plutonic rocks. Because of the different band widths in the VNIR range, Sentinel-2A classifications have the highest pixel count when compared to ASTER classifications for the same surface areas. During fieldwork, rock samples representing the lithologies and Fe-bearing minerals in the region have been collected and mineralogical-petrographic, geochemical, and XRD analyses have been conducted on these samples. Additionally, for spectral mineral identification and to compare Fe-bearing minerals with other analysis results, spectral signatures have also been obtained from the same samples via Analytical Spectral Device (ASD). In extracting features such as lineaments and faults, which play a crucial role in the development of ore deposits along the structural discontinuities, digital elevation models (DEM) have been preferred instead of optical images. When lineament analysis results and iron deposits, which had been identified in previous studies, were overlapped, it has been detected that revealed iron deposits are predominantly associated with the Ciritbelen-Otmangölü Fault (COF) which is an approximately east-west trending strike-slip fault located in the study area, along with other related fault systems. They are generally distributed within an ophiolitic slice and the surrounding magmatic intrusions. Highlights: Fe-bearing formations are predominantly associated with faults and fractures. More healthier classification results were provided with ASTER imagery. Lithological boundaries were revealed with the aid of ASTER 731/RGB band combination. Petrographic, geochemical, and XRD analyses were conducted on the same samples. [ABSTRACT FROM AUTHOR]

Copyright of Acta Petrologica et Mineralogica / Yanshi Kuangwuxue Zazhi is the property of Acta Petrologica et Mineralogica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present work enhances mineral exploration in Egypt’s Eastern Desert by mapping lithological units and identifying hydrothermal alteration zones, potentially leading to the discovery of economically viable mineral deposits. This study employs a comprehensive approach of integrating multispectral bands from Landsat-9 and ASTER images with airborne radiometric data. Various image enhancement techniques such as False Color Composite (FCC), Minimum Noise Fraction (MNF), and Principal Component Analysis (PCA) are utilized to map enhanced lithological units. Additionally, image classification techniques, including Spectral Angle Mapper (SAM) and Crosta Principal Component (CROSTA PC), are applied to emphasize hydrothermal alteration minerals like alunite, calcite, hematite, illite, chlorite, epidote, kaolinite, montmorillonite, and sericite. Furthermore, radioelement ratios (eU/eTh, eU/K, eTh/K, and eU-(eTh/3.5)) and the F-parameter (K*(eU/eTh)) are utilized. Mineral percentages are determined using Scanning Electron Microscope (SEM), allowing for the observation of ore minerals from the Elkharaza-Dara area deposits, which exhibit varying compositions. Maximum values are recorded for specific elements: aluminum (10.48 wt% Al), silicon (65.38 wt% Si), silver (0.32 wt% Ag), copper (2.65 wt% Cu), gold (5.25 wt% Au), potassium (4.32 wt% K), hafnium (3.84 wt% Hf), calcium (26.94 wt% Ca), carbon (56.92 wt% C), and oxygen (53.71 wt% O). These findings offer valuable insights into the elemental composition of the mineralized deposits in the study area. The multi-algorithm integration approach has been confirmed through various methods, including comparison with existing geological maps, fieldwork, and microscopic analysis of selected samples from alteration zones across the study area.

Abstract The present study aimed to delineate a robust watershed boundary and extract its morphometric parameters in the Karnaphuli watershed, Bangladesh, using different digital elevation models (DEMs). Two DEMs, the shuttle radar topographic mission (SRTM) and the terra advanced spaceborne thermal emission and reflection radiometer (ASTER), were employed to delineate watershed boundaries and evaluate various morphometric characteristics. Raster data such as fill sinks, flow direction, and flow accumulation were utilized to delineate the watershed. The morphometric analysis included the estimation of linear, areal, and relief parameters. The findings revealed a noticeable difference between the datasets; ASTER delineated a larger watershed area than SRTM. Regarding stream order, there were streams ranging from 1st to 6th order, encompassing numerous small, medium, and main channels of the river. Drainage density was calculated as 0.52 km/km² for SRTM and 0.51 km/km² for ASTER, both having a spatial resolution of 30 m. The bifurcation ratio ranged from 1.94 for SRTM to 2.45 for ASTER, indicating varying degrees of structural disturbance influenced by geological factors. The form factor indicated an elongated shape of the study area. The overall dimensions of the streams and the watershed extent suggest moderate mean annual rainfall discharge. The watershed exhibited relatively high denudation rates, attributed to the basin relief. A low drainage density indicated the importance of infiltration processes. The findings of this study provide valuable insights into the spatial variability of watershed characteristics, highlighting the need for tailored management strategies for the Karnaphuli River. Implementing targeted conservation measures and watershed management practices based on these morphometric parameters can enhance water resource sustainability and ecological health in the region.

Abstract Granites are widely distributed, phaneritic igneous rocks renowned for their high compressive strength and durability, making them a premier choice for dimension stone applications. This study aims to detect and map granitic complexes using geospatial data and spectral algorithms within the arid and semi-arid environment of northwestern Parwan Province, northeastern Afghanistan. Also, to establish an effective and optimized supervised classification approach specifically tailored for identifying granitic complexes in similar terrains. This study utilizes FCC imagery to highlight lithology and employs various machine learning algorithms, including ML, MD, SVM, and SAM, for mapping granitic complexes within the study area. Training and test data were collected from field observations, Google Earth imagery, and geological maps. Our analysis identified two primary granitic complexes within the study area, measuring approximately 19 km × 13 km2 and 7 km × 3 km2, respectively. Ground truth data validation yielded an accuracy of 75%, indicating a positive correlation between the predicted and observed distributions. This enhanced understanding of granite distribution can serve as a valuable guide for future exploration endeavors targeting metallic and non-metallic resources, including aluminum, iron, manganese, rare earth elements, tungsten, etc.

In recent times, geological remote sensing has greatly enhanced the ability to access alteration zones and identify potential sites for hydrothermal deposits quickly and cost-effectively. This study will utilize satellite image processing methods to map the alteration zones in exploration area of the Zafarghand. The study area is located in the NE of Isfahan and falls within the central structural zone of Iran. The Zafarghand porphyry system exhibits phyllic, potassic, propylitic, argillic alteration halos. Alterations in this study were detected using ASTER sensor imagery. Each pixel's digital number value from the satellite images, organized in a matrix, serves as a sample in a systematic grid. The singularity method algorithm was then applied as an effective structural tool to identify geochemical anomalies in the digital pixel values from ASTER images. The findings demonstrate that the singularity method, due to its structural attributes, has been successful in decision-making and highly effective to determine promising areas in the study area, especially for propylitic and phyllic alterations.

In recent times, geological remote sensing has greatly enhanced the ability to access alteration zones and identify potential sites for hydrothermal deposits quickly and cost-effectively. This study utilizes satellite image processing methods to map the alteration zones in the exploration area of the Zafarghand. The study area is located in the NE of Isfahan and falls within the central structural zone of Iran. The Zafarghand porphyry system exhibits phyllic, potassic, propylitic, and argillic alteration halos. Alterations in this study were detected using ASTER sensor imagery. Each pixel's digital number value from the satellite images, organized in a matrix, serves as a sample in a systematic grid. The singularity method algorithm was then applied as an effective structural tool to identify geochemical anomalies in the digital pixel values from ASTER images. The findings demonstrate that the singularity method, due to its structural attributes, has been successful in decision-making and highly effective on determining promising areas in the study area, especially for propylitic and phyllic alterations. [ABSTRACT FROM AUTHOR]

Palu segment is a part of the East Anatolian Fault Zone (EAFZ), the most important active left-lateral strike-slip fault system in Turkey, and there are different mineral alterations in this zone. The study tested the spatial relationship between tectonic activity and mineral alterations with the Getis-Ord Gi* statistic in and around the Palu segment. Mineral alterations at the pixel level were determined from ASTER images by Ratio, Relative Band Depth (RBD), Mineral Indices, CROSTA, Constrained Energy Minimization (CEM), Mixed Tuned Matched Filter (MTMF) methods. According to the results, the spatial distribution of alteration minerals extend parallel to tectonically active fault lines and/or partially bounded by faults in the area. RBD, Mineral Indices, CROSTA, CEM, and MTMF image processing algorithms applied in the study gave consistent results in the spatial determination and mapping of mineral alterations. At 99% and 95% confidence intervals, statistically significant cold spot clusters indicate the proximity of alterations to faults concentrated around fault lines. This degree of clustering of mineral alterations indicates regions with high alteration rates close to fault lines and areas with tectonic activity along fault lines. [ABSTRACT FROM AUTHOR]

This study integrates Remote Sensing data, field investigation, and petrography to analyze the Zawar Pb–Zn sulfide deposits, in the Paleoproterozoic Aravalli Supergroup rocks of NW India. Structural features of the study area are delineated using Remote Sensing and Shuttle Radar Topography Mission (SRTM) data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, is used to distinguish the major rock types and alteration zones. Our findings reveal that the Zawar belt is composed of phyllite, quartzite, carbonate, and, greywacke. Phyllites from the hinge of the Main Zawar Fold (MZF) provide critical insights into the distribution of monazite veins, and, support the evidence of hydrothermal alteration over the hinge area of the MZF. Textural evidence investigated by Scanning Electron Microscopic study (SEM) suggests that the monazite is of epigenetic hydrothermal origin, formed subsequently after the formation of the primary host rock. Energy Dispersive X-ray spectroscopic (EDS) study indicates that these monazites have an average composition, P2O5(17.85 wt.%), Ce2O3 14.49, La2O3 6.98, Nd2O3 5.39 and ThO2 1.60 wt.%, suggesting its hydrothermal origin. [ABSTRACT FROM AUTHOR]

One of the critical factors influencing the accuracy of a local geoid model is the quality of the digital elevation model (DEM). A properly selected high-resolution DEM can significantly mitigate errors in geoid modeling, gravity anomaly processing, and topography and downward continuation correction. Purpose. Evaluating the accuracy of five global DEMs obtained from open sources to identify the most suitable model for creating a local geoid. Methodology. The vertical accuracy of the DEMs was assessed by comparing the heights between the DEM and control points across different types of terrain. The reference values are based on 344 ground benchmarks, where GNSS observations were performed with subsequent adjustment of coordinates and heights. The accuracy analysis involved calculating statistical indicators of the height differences between the GNSS data and the DEM data. Findings. The standard deviation assessment showed favorable values for the COPERNICUS and ALOS DEMs, followed by SRTM, ASTER, and ETOPO. In the mean absolute error calculations for mountainous areas, the ALOS model performed best, followed by COPERNICUS, SRTM, ASTER, and ETOPO. For other types of terrain, COPERNICUS demonstrated the best results in mean absolute error. Originality. This study distinguishes itself through the incorporation of advanced high-resolution DEMs, such as GLO30, providing a modern and thorough evaluation of DEM accuracy specifically for Kazakhstan. What is new is a detailed analysis of the impact of terrain features (plain, hilly, mountainous) on modeling accuracy. This approach advances beyond previous assessments, delivering new and significant insights into the performance of contemporary DEMs. Practice value. The practical value of the results obtained consists in issuing recommendations regarding the possibility of using the studied DEM for the regions of Kazakhstan which differ among themselves in terms of landscape characteristics. The findings indicate that COPERNICUS and ALOS DEMs are highly suitable for precise geoid modeling in southern Kazakhstan. These models can significantly improve the accuracy of local geoid models, benefiting applications in geospatial science and engineering. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Validation studies of global Digital Elevation Models (DEMs) in the existing literature are limited by the diversity and spread of landscapes, terrain types considered and sparseness of groundtruth. Moreover, there are knowledge gaps on the accuracy variations in rugged and complex landscapes, and previous studies have often not relied on robust internal and external validation measures. Thus, there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications. In this study, we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution, readily available, free-access and global coverage 1 arc-second (30 m) DEMs: NASADEM, ASTER GDEM, Copernicus GLO-30, and ALOS World 3D (AW3D). The assessment is carried out at landscapes spread across Cape Town, Southern Africa (urban/industrial, agricultural, mountain, peninsula and grassland/shrubland) and forested national parks in Gabon, Central Africa (low-relief tropical rainforest and high-relief tropical rainforest). The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution, and error ranking. In Cape Town, Copernicus DEM generally had the least vertical error with an overall Mean Error (ME) of 0.82 m and Root Mean Square Error (RMSE) of 2.34 m while ASTER DEM had the poorest performance. However, ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon. Generally, the DEM errors have a moderate to high positive correlation in forests, and a low to moderate positive correlation in mountains and urban areas. Copernicus DEM showed superior vertical accuracy in forests with less than 40% tree cover, while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%. This study is a robust regional assessment of these global DEMs. [ABSTRACT FROM AUTHOR]

Quantifying the volume of erupted volcanic material, particularly lava flows and domes, provides critical insights into the dynamics of an eruption. This in turn aids in future hazard modeling, mitigation, and response. However, acquiring the necessary topographic datasets to calculate volumetric change is difficult, especially for active volcanoes in remote regions. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument has acquired global photogrammetric data since 2000, from which individual scene digital elevation models (DEMs) are created. We present a new straight forward method using ASTER DEMs to measure the volume of emplaced lava flows, domes, and tephra cones. We focus on five case studies that represent different eruption styles and products. For each of these we compare the results to those from previous studies that used alternative topographic datasets, such as synthetic aperture radar (SAR), airborne photogrammetry, or Light Detection and Ranging (LiDAR) measurements. These datasets, however, are expensive to acquire or lack the needed temporal resolution. We show that in nearly all cases, our volume results are either within the reported range for the eruption or ≤0.05 km3 of the previously reported value derived from SAR or LiDAR. The simplicity of the ASTER DEM approach combined with the global coverage of the data products enables more timely production of accurate volumetric data during and following an eruption, which can then be used to assess past and future eruption dynamics.

Alteration minerals and silicification are typically associated with a variety of ore mineralizations and could be detected using multispectral remote sensing sensors as indicators for mineral exploration. In this investigation, the Visible Near-Infra-Red (VNIR), Short-Wave Infra-Red (SWIR), and Thermal Infra-Red (TIR) bands of the ASTER satellite sensor derived layers were fused to detect alteration minerals and silicification in east the Kerdous inlier for cupriferous mineralization exploration. Several image processing techniques were executed in the present investigation, namely, Band Ratio (BR), Selective Principal Component Analysis (SPCA) and Constrained Energy Minimization (CEM) techniques. Initially, the BR and SPCA processing results revealed several alteration zones, including argillic, phyllic, dolomitization and silicification as well as iron oxides and hydroxides. Then, these zones were mapped at sub-pixel level using the CEM technique. Pyrophyllite, kaolinite, dolomite, illite, muscovite, montmorillonite, topaz and hematite were revealed displaying a significant distribution in relation with the eastern Amlen region lithological units and previously detected mineral potential zones using HyMap imaging spectroscopy. Mainly, a close spatial association between iron oxides and hydroxide minerals, argillic, and phyllic alteration was detected, as well as a strong silicification was detected around doleritic dykes unit in Jbel Lkest area. A weighted overlay approach was used in the integration of hydrothermal alteration minerals and silicification, which allowed the elaboration of a new mineral alteration map of study area with five alteration intensities. ASTER and the various employed processing techniques allowed a practical and cost effective mapping of alteration features, which corroborates well with field survey and X-ray diffraction analysis. Therefore, ASTER data and the employed processing techniques offers a practical approach for mineral prospection in comparable settings.

Validation studies of global Digital Elevation Models (DEMs) in the existing literature are limited by the diversity and spread of landscapes, terrain types considered and sparseness of groundtruth. Moreover, there are knowledge gaps on the accuracy variations in rugged and complex landscapes, and previous studies have often not relied on robust internal and external validation measures. Thus, there is still only partial understanding and limited perspective of the reliability and adequacy of global DEMs for several applications. In this study, we utilize a dense spread of LiDAR groundtruth to assess the vertical accuracies of four medium-resolution, readily available, free-access and global coverage 1 arc-second (30 m) DEMs: NASADEM, ASTER GDEM, Copernicus GLO-30, and ALOS World 3D (AW3D). The assessment is carried out at landscapes spread across Cape Town, Southern Africa (urban/industrial, agricultural, mountain, peninsula and grassland/shrubland) and forested national parks in Gabon, Central Africa (low-relief tropical rainforest and high-relief tropical rainforest). The statistical analysis is based on robust accuracy metrics that cater for normal and non-normal elevation error distribution, and error ranking. In Cape Town, Copernicus DEM generally had the least vertical error with an overall Mean Error (ME) of 0.82 m and Root Mean Square Error (RMSE) of 2.34 m while ASTER DEM had the poorest performance. However, ASTER GDEM and NASADEM performed better in the low-relief and high-relief tropical forests of Gabon. Generally, the DEM errors have a moderate to high positive correlation in forests, and a low to moderate positive correlation in mountains and urban areas. Copernicus DEM showed superior vertical accuracy in forests with less than 40% tree cover, while ASTER and NASADEM performed better in denser forests with tree cover greater than 70%. This study is a robust regional assessment of these global DEMs.

Iron plays an important role in industrial and engineering fields development of a country and as such there is an enormous demand for iron in Ethiopia. However, a search for this valuable primary mineral resource exploration remains challenging and costly. Therefore, this study aims to map iron oxide minerals using Landsat-8/operational land imager (OLI) and advanced space-borne thermal emission and reflection (ASTER) satellite imagery in Negash Lateritic iron deposit, Northern Ethiopia to ease the costs and reduce the time. Different image processing techniques such as band ratio, selective principal component analysis, linear spectral unmixing, and mixture-tuned matched filter were used to produce iron oxide maps. Minimum noise fraction (MNF), pixel purity index (PPI), and N-dimensional visualizer were also applied to extract endmembers in the automated spectral hourglass wizard. In addition to this, the enhanced image thresholding and scatter plot were used to map the potential areas. Ferric iron oxide band ratio of ASTER mapped maximum area of 62.1 km2 followed by a laterite band ratio of ASTER covering 57.8 km2. The result was validated using existing iron oxide polygons and the outcome obtained from selective PCA shows a strong match with the existing iron oxide polygons. The sub-pixel mapping techniques show poor accuracy in mapping goethite and hematite relative to the pixel level. Thus, it is evident from the results that ASTER mapped better than Landsat 8 OLI for band ratios of selective PCA, unmixing, MTMF, and mineralized areas while characterizing with limited fieldwork.

Semna area is located within the Golden Triangle district in the Central Eastern Desert of Egypt. The study maintains using multisource datasets of remote sensing, aero-spectrometry, aero-magnetic, and field investigations for unraveling the ambiguities associated with the alteration zones at the targeted area. Three remote sensing mapping techniques including; constrained energy minimization, linear spectral unmixing, and mineral indices, were adopted to delineate the alteration zones. The γ-ray spectrometry data of K (%), K/eTh, K/eU, and F-parameter enabled mapping the potassium-enriched localities as indication on possible potassic alteration zones. The surface and subsurface linear structural features were delineated from the digital elevation model and aero-magnetic data, respectively. The outcomes of all the implemented datasets were integrated using GIS overlay modeling, producing an integrated mineralization favorability/potentiality map. Eighteen localities with high potential for mineralization were highlighted. A field study was conducted to the investigated area during which, several alteration indicators were observed, including quartz veins, iron oxides staining, kaolinite, malachite, carbonate, and muscovite (sericite) alteration indicator minerals.

The exploration of Pb-Zn mineralization in carbonate complexes during field campaign is a challenging process that consumes high expenses and time to discover high prospective zones for a detailed exploration stage. In this study, multi-sensor remote-sensing imagery from Landsat-8, Sentinel-2, and ASTER were utilized for Pb-Zn mineralization prospectivity mapping in the Akhlamad carbonate complex area, Razavi Khorasan, NE Iran. Due to the presence of carbonate formations and various evidence of Pb-Zn mineralization, this area was selected. Band composition, band ratio, principal component analysis (PCA), and SAM techniques for mapping alteration minerals as well as lineament analysis were implemented. Subsequently, a fuzzy logic model for identifying the prospective zones of Pb-Zn mineralization using multi-sensor remote-sensing satellite images was designed. The weight of each exploratory layer was determined using the fuzzy hierarchical method and the integration process of the information layers was performed using fuzzy operators. Finally, the existing mineral indications were used to evaluate and validate the obtained mineral potential map. The outcome of this investigation suggested several high-potential zones for Pb-Zn exploration in the study area.

Albedo plays a critical role in the mass balance of a glacier, as it affects its ablation. In this work, the remotely sensed albedo dynamics of Turbio and Pedregoso glaciers of the Villarrica Volcano were assessed, after the occurrence of a large-magnitude eruptive event in 2015, which partially covered them of tephras. The albedo was derived from eight ASTER (Advanced Spaceborn Thermal Emission and Reflection Radiometer) satellite images, acquired on near-anniversary summer dates before, during and after the mentioned event (2009-2022). The temporal behavior of the ex-post albedo of both studied glaciers tended to predominantly decrease, especially in their ablation zones. They are subject to greater surface exposure of the tephra deposits, in response to the cyclical melting/sublimation experienced during the summer by the snowpack succeed in cover them during the rest of the year. This decrease reached its maximum value in 2002, likely due to the extremely singular warmth and drought recorded in the previous year in the study area. It is expected that these results will contribute to understand the ex-post dynamics of the albedo in the study area, in terms of its magnitude and pervasiveness over time. This may provide valuable information for tracking and prospecting the mass balances of both studied glaciers. [ABSTRACT FROM AUTHOR]

In this study, the satellite data of ASTER and Landsat 8 OLI were used for the discrimination of lithological units covering the Khyber range. Of the 24 tested band combinations, the most suitable include 632 and 468 of ASTER and 754 and 147 of OLI in the RGB sequence. The data were also tested with two conventional machine learning algorithms (MLAs), namely maximum likelihood classification (MLC) and support vector machine (SVM), for lithological mapping. Principal component analysis (PCA), minimum noise fraction (MNF), band ratios, and color composites in combination with available lithological maps and field data were utilized for training sample collection for the MLC and SVM models to classify the lithological units. The accuracy assessment of SVM and MLC was performed using a confusion matrix, which revealed a higher accuracy of 74.8419% and 72.1217% for ASTER and an accuracy of 58.4833% and 60.0257% for OLI, respectively. The results indicate that ASTER imagery is more suitable for lithological discrimination in the study area due to its high spectral resolution in the VNIR to SWIR range. The experiment revealed that the SVM classification offered the highest overall accuracy of nearly 75% and the kappa coefficient value of 0.7 on ASTER data. This demonstrates the effectiveness of SVM classification in exploring lithological mapping in dry to semi-arid regions. [ABSTRACT FROM AUTHOR]

At hydrothermal systems, heat transfer across the final surface layer is driven by permeable convection and conduction, so that soil permeability and thermal conductivity play fundamental roles in controlling heat flux to the atmosphere. We build a Rayleigh-number driven heat transfer model for a bottom-heated surface that uses measurements of heat flux density (radiation and convection to the atmosphere in W/m2), surface temperature, and soil temperature to solve for soil conductivity, density, and permeability for such a bottom-heated surface. At Vulcano in 2019, we measured an ASTER-derived heat flux density of 240 ± 70 W/m2 and a difference between soil and surface temperature of 18 ± 6 °C. The surface layer is a 7.5 ± 2.5 cm thick case-hardened crust across which heat transfer is conduction dominated. We invert our heat transfer model using the temperature (T) gradient derived from a trench dug into the soil: T = − 49.7y2 + 113.6y + 35 (R2 = 0.9997), where y is depth in meters between the surface and 70 cm. The result is a conductivity for the case-hardened surface layer of 1.0 ± 0.3 W/(m K) and a density of 2440 ± 120 kg/m3. Below this case-hardened crust, heat transfer is dominated by permeable convection in a soil comprised of highly altered trachytic blocks in an ash matrix. Our model gives permeabilities of 1–19 × 10−10 m2 for this layer in 2019. In 2021, Vulcano entered a phase of unrest. Our model reveals that this was associated with an increase in permeability to 10−7 m2. However, by 2023 permeabilities had reverted to pre-unrest levels. Using simple measurements of surface and soil temperature, coupled with heat flux density from a satellite overpass, the model can be used as a basis to constrain heat transfer and to assess permeability at any hydrothermal system. [ABSTRACT FROM AUTHOR]

Semna area is located within the Golden Triangle district in the Central Eastern Desert of Egypt. The study maintains using multisource datasets of remote sensing, aero-spectrometry, aero-magnetic, and field investigations for unraveling the ambiguities associated with the alteration zones at the targeted area. Three remote sensing mapping techniques including; constrained energy minimization, linear spectral unmixing, and mineral indices, were adopted to delineate the alteration zones. The γ-ray spectrometry data of K (%), K/eTh, K/eU, and F-parameter enabled mapping the potassium-enriched localities as indication on possible potassic alteration zones. The surface and subsurface linear structural features were delineated from the digital elevation model and aero-magnetic data, respectively. The outcomes of all the implemented datasets were integrated using GIS overlay modeling, producing an integrated mineralization favorability/potentiality map. Eighteen localities with high potential for mineralization were highlighted. A field study was conducted to the investigated area during which, several alteration indicators were observed, including quartz veins, iron oxides staining, kaolinite, malachite, carbonate, and muscovite (sericite) alteration indicator minerals. [ABSTRACT FROM AUTHOR]

The exploration of Pb-Zn mineralization in carbonate complexes during field campaign is a challenging process that consumes high expenses and time to discover high prospective zones for a detailed exploration stage. In this study, multi-sensor remote-sensing imagery from Landsat-8, Sentinel-2, and ASTER were utilized for Pb-Zn mineralization prospectivity mapping in the Akhlamad carbonate complex area, Razavi Khorasan, NE Iran. Due to the presence of carbonate formations and various evidence of Pb-Zn mineralization, this area was selected. Band composition, band ratio, principal component analysis (PCA), and SAM techniques for mapping alteration minerals as well as lineament analysis were implemented. Subsequently, a fuzzy logic model for identifying the prospective zones of Pb-Zn mineralization using multi-sensor remote-sensing satellite images was designed. The weight of each exploratory layer was determined using the fuzzy hierarchical method and the integration process of the information layers was performed using fuzzy operators. Finally, the existing mineral indications were used to evaluate and validate the obtained mineral potential map. The outcome of this investigation suggested several high-potential zones for Pb-Zn exploration in the study area. [ABSTRACT FROM AUTHOR]

This research applies remote sensing methodologies for the first time to comprehensively explore the geological and mineralogical characteristics of the Jbel Bou Dahar region. An integrated approach with multi-sensor satellite images, including ASTER, Landsat-8, and Sentinel-2 was applied with the aim to discriminate the different lithological units in the study area. We implemented a suite of well-established image processing techniques, including Band Ratios, Principal Component Analysis, and Spectral Angle Mapper, to successfully identify, classify, and map the spatial distribution of carbonate minerals, OH-bearing minerals, and iron oxide minerals. Due to its high spectral resolution in the short-wave infrared region (SWIR), the ASTER sensor provided the most accurate results for mapping carbonate and OH-bearing minerals compared to the Sentinel-2 and Landsat-8 sensors. Conversely, Sentinel-2 offers high spectral and spatial resolution in visible and near-infrared (VNIR) corresponding to the regions where iron oxide minerals exhibit their characteristic absorption peaks. The results confirm the advantages of remote sensing technologies in the geological and mineralogical exploration of the study area and the importance of selecting the appropriate sensors for specific mapping objectives. [ABSTRACT FROM AUTHOR]

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional "wet" and "dry" zones that appear to express "deep" geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant "muscovite" that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the "lowlands" of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding "uplands", such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues. [ABSTRACT FROM AUTHOR]

Aster L. is an economically and phylogenetically important genus in the tribe Astereae. Here, the complete plastomes of the eight Aster species were assembled and characterized using next-generation sequencing datasets. The results indicated the complete plastomes of Aster had a quadripartite structure. These genomes were 152,045-152,729 bp in length and contained 132-133 genes, including 87 protein-coding genes, 37-38 tRNA genes, and eight rRNA genes. Expansion or contraction of inverted repeat regions and forward, palindromic, complement, and reverse repeats were detected in the eight Aster species. Additionally, our analyses showed the richest type of simple sequence repeats was A/T mononucleotides, and 14 highly variable regions were discovered by analyzing the border regions, sequence divergence, and hotspots. Phylogenetic analyses indicated that 27 species in Astereae were clustered into six clades, i.e., A to D, North American, and outgroup clades, and supported that the genera Heteropappus, Kalimeris, and Heteroplexis are nested within Aster. The results indicated the clades B to D might be considered as genera. Divergence time estimate showed the clades A, B, C, and D diverged at 23.15 Mya, 15.13 Mya, 24.29 Mya, and 21.66 Mya, respectively. These results shed light on the phylogenetic relationships of Aster and provided new information on species identification of Aster and its related genera. [ABSTRACT FROM AUTHOR]

El albedo juega un rol crítico en el balance de masa de un glaciar, por cuanto incide en su ablación. En este trabajo fue evaluada la dinámica del albedo teledetectado de los glaciares Turbio y Pedregoso del Volcán Villarrica, luego de ocurrido un evento eruptivo de gran magnitud en 2015, que significó su recubrimiento parcial de tefras. El albedo fue derivado desde ocho imágenes satelitales ASTER (Advanced Spaceborn Thermal Emission and Reflection Radiometer), adquiridas en fechas estivales de casi-aniversario antes, durante y después del evento en cuestión (2009-2022). El comportamiento temporal del albedo ex-post de ambos glaciares estudiados tendió predominantemente a la baja, en especial en sus zonas de ablación, sujetas a mayor exposición superficial de los depósitos de tefras, en respuesta al derretimiento/sublimación cíclica que experimenta durante el estío la capa nival que logra recubrirlos el resto del año. Este decremento alcanzó su valor máximo en 2002, presumiblemente a causa de la extremadamente singular calidez y sequía registrada a lo largo del año precedente en el área de estudio. Se espera que estos resultados contribuyan a comprender la dinámica ex-post del albedo en el área de estudio, en términos de su magnitud y pervasividad en el tiempo, a fin de aportar valiosa información para el rastreo y prospección de los balances de masa de ambos glaciares estudiados.

This research applies remote sensing methodologies for the first time to comprehensively explore the geological and mineralogical characteristics of the Jbel Bou Dahar region. An integrated approach with multi-sensor satellite images, including ASTER, Landsat-8, and Sentinel-2 was applied with the aim to discriminate the different lithological units in the study area. We implemented a suite of well-established image processing techniques, including Band Ratios, Principal Component Analysis, and Spectral Angle Mapper, to successfully identify, classify, and map the spatial distribution of carbonate minerals, OH-bearing minerals, and iron oxide minerals. Due to its high spectral resolution in the short-wave infrared region (SWIR), the ASTER sensor provided the most accurate results for mapping carbonate and OH-bearing minerals compared to the Sentinel-2 and Landsat-8 sensors. Conversely, Sentinel-2 offers high spectral and spatial resolution in visible and near-infrared (VNIR) corresponding to the regions where iron oxide minerals exhibit their characteristic absorption peaks. The results confirm the advantages of remote sensing technologies in the geological and mineralogical exploration of the study area and the importance of selecting the appropriate sensors for specific mapping objectives.

Aster yaoshanensis sp. nov., a new species of the family Asteraceae is here described and illustrated. The species is presently known only from rock crevices of mountain valleys in Dayaoshan National Nature Reserve, Guangxi autonomous region, China. Phylogenetic analyses based on ITS sequences and complete plastome data have shown that this new species is a member of genus Aster with high support. Morphologically, it mostly resembles A. jishouensis, but it can be easily distinguished from the latter by bract indumentum (glabrous except margin ciliate vs. villous especially on veins abaxially, glabrous adaxially) and color (green vs. purple), shorter corolla (3.2-3.5 mm vs. 4.5-5.3 mm), bract stalk (obvious, ca.1.2 mm vs. sessile), and different distribution (Guangxi vs. Hunan). The detailed description, distribution map, and photos are provided. This study further elucidates the species identification, phylogeny and characteristic evolution of Aster. [ABSTRACT FROM AUTHOR]

Among the major classes of plant hormones, auxins, gibberellins, and cytokinins are widely used for plant propagation. These hormones influence the physiological and developmental processes of plants such as root initiation, apical dominance, seed germination, leaf expansion, and development of buds, flowers, and fruits. Its exogenous application was found to significantly improve the growth of several important plants. This study aimed to determine the effectiveness of plant growth regulators (PGRs) derived from naturally occurring plant growth-promoting bacteria (PGPBs) in the production and propagation of selected crops. In this study, indole-3-acetic acid (IAA) and gibberellic acid (GA) were extracted from naturally occurring PGPB Bacillus sp. The extracted hormone was nanoformulated for controlled release and increased uptake in plants. The nanoformulated hormones were applied in the propagation of coffee and the production of eggplant and ornamentals. Results showed that the application of nanoformulated IAA (Nano-IAA) significantly increased the survival rate of coffee compared to the commercially available auxin. Nano-IAA increased the germination rate of eggplant in acidic soil and root emergence of Bougainvillea over the negative control (water) but was comparable to that of the commercially available auxin. The nanoformulated GAs and commercially available GA increased the plant height and weight of asters compared to the control. The study showed the effectiveness of Nano-IAA and GA in the production and propagation of coffee, eggplant, and selected ornamentals. Hence, these nanoformulated PGRs can be a substitute for synthetic and imported IAA and GA in plant production and propagation. [ABSTRACT FROM AUTHOR]

Petroleum accumulations may coincide with either positive or negative temperature anomalies, which are conventionally detected using in situ temperature measurements made in shallow boreholes 1‐3 m deep. Data gathered in this way, however, can be sparse and costly, and may require intensive fieldwork over a long time period. This article explores the possibility of detecting thermal anomalies associated with petroleum entrapment using satellite‐derived land surface temperature data. For this aim, a robust correction scheme based on a physically‐based land surface model was applied to night‐time kinetic temperature data derived from NASA's ASTER instrument. The numerical model, known as SKinTES, attempts to simulate diurnal effects and to remove them from the measured temperature data to yield a residual temperature anomaly map. The performance of this methodology was tested over the Alborz oilfield located on an anticline of the same name in the Qom region of Central Iran. The study area has an arid to semi‐arid climate and the surface geology is dominated by outcrops of the Lower Miocene Upper Red Formation. The modelling approach used successfully highlighted several negative temperature anomalies over the oil‐bearing parts of the Alborz structure. In comparison to the uncorrected data, the anomalies were shown to be highly enhanced in both spatial and magnitude terms. In addition, time series analysis indicated that the temperature anomalies were consistent over time. The authenticity of the anomalies was confirmed by a suite of in situ temperature measurements made at shallow boreholes. In conclusion, a unifying framework is proposed to explain the occurrence of both negative and positive temperature anomalies over petroleum accumulations. The new modelling and correction scheme is expected to broaden the application of remote sensing land surface temperature data not only in petroleum exploration but also in other types of geothermic investigations including geothermal exploration. [ABSTRACT FROM AUTHOR]

The Eastern Taurides, which form the imbrication and nappe zone in the northernmost part of the Arabian platform, are located within the Southeastern Anatolian Orogenic Belt. In the present study, spectral enhancement methods such as band ratioing, minimum noise fraction (MNF), relative band depth (RBD), and supervised classification were applied to ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images of metamorphic massifs, ophiolites, and sedimentary rocks outcropping in the western part of the Eastern Taurides (Göksun, Afşin, and Ekinözü regions). With these methods, the aim was to distinguish geological units from each other accurately. In the study area, arid climatic conditions with relatively poor vegetation, allowing for precise visual interpretations, play a significant role. Vegetation and water bodies were also masked before these procedures. In the Göksun, Afşin, and Ekinözü regions, metamorphic rocks of phyllite, schist, and gneiss types, which underwent metamorphism during the Upper Cretaceous and Eocene periods, are observed. The geologically dominant minerals in these rocks include silica, mica (muscovite, phengite, biotite), chlorite (clinochlore, chamosite), kaolinite, and carbonates (calcite, dolomite). These rocks are accompanied by ophiolitic, volcanic/volcano-sedimentary, and plutonic igneous rocks. Due to geological events during the closure of the Neotethys Ocean and continental collision in the area, it became evident that the lithological diversity from various rock groups was reflected in the ASTER images, in addition to field observations. Image processing analyses applied to the ASTER sensor images, rich in short-wave infrared (SWIR) and thermal infrared (TIR) bands on the Terra platform, revealed distributions of clay, sulfate, carbonate, iron oxide, and silica minerals. The highest geological differentiation potential was observed through ASTER 643 (RGB) and ASTER 13,12,10 (RGB) false-color composites, as well as ASTER 456 (RGB) minimum noise fraction (MNF) analyses and, especially, relative band depth processes. Relative band depth processes were employed to identify epidote-chlorite-amphibole, calcite-chlorite-amphibole, alunite-kaolinitepyrophyllite, muscovite, and silica minerals. The application of these processes revealed lithologies that strongly feature these minerals. Specifically, the goal was to differentiate rock units containing kaolinite, muscovite, phengite, chlorite, and epidote minerals belonging to AlOH and FeOH groups and elucidate their compositions. Moreover, rocks containing primarily quartz and feldspar were distinguished using ASTER TIR bands. The obtained data revealed that mineralogical and corresponding lithological spatial distributions, as depicted by ASTER images, could play a crucial role in geological mapping, particularly in regions where mapping is challenging due to geographical conditions. [ABSTRACT FROM AUTHOR]

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This study evaluates and compares the accuracy and reliability of multiple freely available digital elevation models (DEMs) including Copernicus Global Land Operations (GLO), Advanced Land Observing Satellite (ALOS), Cartosat, Shuttle Radar Topography Mission (SRTM), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for hydrological applications in the Mahi River upper basin in Western India. Through watershed delineation, statistical analysis, error quantification, and 2D hydraulic modeling using HEC-RAS, this research assesses the performance of these DEMs with GLO DEM as the reference. GLO DEM is used as the reference because key findings show it most accurately delineates watershed boundaries and stream networks and has the fewest sinks. ALOS also demonstrates strong performance, with 70.47% watershed boundary similarity to GLO. Cartosat shows reasonable accuracy in watershed delineation with a Jaccard Index (JI) of 68.41% while SRTM and ASTER appear less reliable. Statistical analysis reveals ALOS slightly overestimates while other DEMs underestimate elevations compared to GLO for most of the slope classes. Flood modeling shows GLO produces the smoothest inundation, with ALOS second-best. Overall, GLO and ALOS emerge as the most accurate and reliable options followed by Cartosat among freely available datasets for the study area. The research provides insights into DEM performance to inform selection and improve hydrological applications involving terrain data for the study area. [ABSTRACT FROM AUTHOR]