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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]

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]

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]

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.

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]

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.

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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]

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]

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.

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.

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.

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.

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]

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]

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]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office 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.)

Delineating and mapping alteration zones in porphyry copper exploration is of special importance. In this study, satellite image processing techniques were employed to highlight alteration zones in the Zafarghand exploration area. The Zafarghand area is located in the southeastern part of Ardestan and the northwestern part of Isfahan. It is situated within the geological structural zones of central Iran and the intermediate magmatic arc of Urmia-Dokhtar. Various alteration haloes are present in this area, including phyllic, potassic, propylitic, argillic, and slightly siliceous alterations. In this study, the detection of related alterations was carried out using ASTER sensor imagery. Accordingly, considering the raster nature and digital form of satellite images, the digital number values of each pixel from the image matrices were considered as samples in a systematic network. Finally, the U spatial statistic algorithm was implemented as a moving window algorithm for determining anomaly samples in the set of digital number (DN) values of ASTER satellite image pixels. The results of this technique show that the application of the U-statistic method, considering its structural nature and neighboring samples in decision-making, has been successful and has proven to be very effective in determining the alteration zones in the Zafarghand area. It could be observed the delineated propylitic alteration by the U-statistic method is closely associated with the defined zone of propylitic alteration, which is also consistent with the field and microscopic observation of the porphyry Cu mineralization in this alteration zone. It is also observed that the determined phyllic alteration by this image processing is spatially conformable with the sericitic alteration presented in the alteration map (based on field observations and geochemical sampling).

Digital elevation models (DEMs) are crucial for numerous assessments of the Earth's surface, so this research aim to evaluate the quality of several open source DEMs like advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTM DEM), SENTINEL-1, and TerraSAR-X for digital elevation measurement (TanDEM-X). TanDEM-X is one of the newest DEM models; however, ASTER and SRTM are still the most used. To evaluate the qualities of these DEMs, the vertical accuracies of ASTER, STRM (all 30 m), SRTM, TanDEM-X (90 m), and SENTINEL 1 (range from 5 to 12.5 m) were tested using GPS reference points and The RMSE gave the values of ± 3.56 m ± 57.68 m, ±5.89 m, ±10.21 m and ± 20.25 m for used SRTM1, SENTINEL-1, SRTM3, TanDEM-X, and ASTER DEMs respectively. As is well known, obtaining a high-quality DEM is exceedingly challenging since it is time-consuming, expensive, and often constrained, therefore this study examined how to enhance SRTM1 as it gave the best result and assessed the effects of increasing the number of points on digital elevation model accuracy by using raster calculator and merge model in ArcGIS. The results showed that the merge model method gave the best result and, by increasing the number of reference points, the accuracy increased. The DEM produced by the enhanced SRTM (iSRTM) demonstrated noticeably better outcomes than the baseline SRTM DEM, with around 3.56 m RMSE.In this research, STRM-1 DEM is used to determine watershed basin delineation. The topographic map showed significant variations in the level of the Earth's surface, as the heights of the area ranged between 20 m and 120 m. The number of watersheds extracted in the Benban is 132 with different areas, the large area is about 72.14 km2, while the small area is about 1.13 km2, and between those areas, there are various areas. The largest recorded watershed circumference reached 48.94 km in area (72.14 km2), while the lowest recorded perimeter is 5.40 km for the area (1.13 km2).

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

Spectral mixing is frequently encountered in remotely sensed images while imaging heterogeneous surfaces. Spectral mixing occurs at the macroscopic level due to the sensor's low spatial resolution or multiple reflections from materials received by the sensor. Due to the mixing effect, retrieving the information of spectral endmembers becomes complicated. In this study, two different unmixing methods: (i) linear mixing models (LMM) and (ii) the Hapke nonlinear mixing model, were used to quantitatively estimate the fractional abundance of various rock types that will be helpful in remotely mapping the mineral prospects. Three types of constraints using the least square approach were applied independently to LMM and Hapke models, namely FCLS (sum to unity and nonnegativity constrained), NNLS (nonnegativity constrained), and UCLS (unconstrained). AVIRIS-NG (Airborne Visible and InfraRed Imaging Spectrometer-Next Generation) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images from the Sittampundi anorthosite complex (SAC) were utilised for the spectral mixture analysis. Few studies are available on the anorthosite rocks of Sittampundi as an analogue to the Lunar anorthosite. The study area is known for its chromite deposits occurring in pyroxenite rocks. Therefore, in the present study, endmembers considered are anorthosite and pyroxenite/metagabbro. The moderately dense vegetation cover of the study area obscures the detection of rock outcrops on the surface. The study area exhibits nonlinear spectral mixing effects due to the vegetation cover. Hence apart from the two rock endmembers, vegetation is also considered as an endmembers in spectral mixture analysis. The results show a high fractional abundance of vegetation and anorthosite throughout the study region, with the pyroxenite/metagabbro mainly concentrated over the western and eastern regions. The Hapke model shows more accurate results than LMM on the AVIRIS-NG image. The Hapke model outperforms LMM in accurately retrieving the fractional abundance of endmembers due to the nonlinear spectral mixing effects caused by vegetation. Additionally, the constrained least squares methods, i.e., FCLS and NNLS, performed better than UCLS in linear and nonlinear mixing models, resulting in accurate and reliable abundance maps. AVIRIS-NG outperformed the ASTER images in fractional abundance mapping of endmembers, highlighting the importance of utilising higher spatial and spectral resolution data for more reliable land cover and lithology mapping. Overall, this study demonstrates the potential of spectral mixture analysis in identifying geologic outcrops in vegetation-covered regions. Hence, the methodology presented in this study benefits the lithological mapping of vegetation-covered regions and has wide applications in quantitatively assessing the lithology of mineral prospects. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive intercomparison study investigating the radiometric performance of and concurrence among the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat 8 Operational Land Imager (L8 OLI), and Landsat 9 OLI (L9 OLI) instruments. This study leverages data sourced from the Radiometric Calibration Network (RadCalNet) and focuses on spectral bands relevant for vegetation analysis and land cover classification, encompassing a thorough assessment of data quality, uncertainties, and underlying influencing factors. This study's outcomes underscore the efficacy of RadCalNet in evaluating the precision and reliability of remote sensing data, offering valuable insights into the strengths and limitations of ASTER, L8 OLI, and L9 OLI. These insights serve as a foundation for informed decision making in environmental monitoring and resource management, highlighting the pivotal role of RadCalNet in gauging the radiometric performance of remote sensing sensors. Results from RadCalNet sites, namely Railroad Valley Playa and Gobabeb, show their possible suitability for sensors with spatial resolutions down to 15 m. The results indicate that the measurements from both ASTER and OLI closely align with the data from RadCalNet, and the observed agreement falls comfortably within the total range of potential errors associated with the sensors and the test site information. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Architectural Sciences & Applications (JASA) is the property of Journal of Architectural Sciences & Applications 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 Dasuji giant porphyry molybdenum deposit is one of the largest ore deposits recently discovered along the Yinshan–Yanshan–Liaoning molybdenum belt in China. Using this deposit along the Yinshan–Yanshan–Liaoning molybdenum belt as the study area, the present study proposed a two-stage approach aimed at marking out the hydrothermally altered anomalies in the study area for the guidance of future prospecting in other regions. First of all, the Principal Component Analysis (PCA) and specific Band Ratio methods were applied to the ASTER images from different acquisition dates to extract ferric oxides and hydroxyl alterations related to the porphyry molybdenum deposit. Then, the Fractal-Aided Anomaly-Overlaying Selection model was adopted to recognize two ferric and hydroxyl alteration layers for separating anomalies from the interferences caused by geology and random noise from the data. Furthermore, for lithological differentiation in the previously marked off area, the Random Forest Classifier (RFC) was applied to the composite data obtained via the ASTER, ETM, and DEM, and it is demonstrated that the DEM can significantly improve lithological mapping in areas with complex vegetation cover and topography. Based on field verification and comparison with geological maps, the research revealed that the suggested two-stage approach may effectively reduce erroneously recognized anomalies produced during the first stage while retaining ore-related anomalies for gigantic porphyry molybdenum deposit prospecting in the Dasuji area, which showed the good application potential of the proposed model to extract actual hydrothermally altered anomalies adopted for lithological discrimination and mapping. [ABSTRACT FROM AUTHOR]

The Goriganga river basin lies in the Northeast Kumaon Himalaya and is found suitable for assessing active tectonics at different scales. In addition, this study focuses on the assessment of ongoing tectonic activity through morphotectonic measurement of the Goriganga river basin, which is an ideal location for such analysis and Goriganga river basin transects with three major domains of Himalaya's lithotectonic structures viz., Tethys, Vaikrita, and Lesser Himalayan Domain. To realize this task, the ASTER Digital Elevation Model was used and found suitable to extract different morphotectonic indices such as Stream Length Gradient (SL), Hypsometric Integral (HI), Length of Overland Flow (Lg), Drainage Density (Dd) and Channel Sinuosity (Cs). Results of these important indices, including SL (18-4737) HI (0.26-0.57), and Lg (0.08-0.19) depict greater variability in the tectonics activity while these values are correspondingly high in the close proximity of lithotectonic units, showing strong tectonic activity. In the extreme south, the Rauntis Gad basin strongly influences tectonism due to transecting syncline and anticline as well as unknown active faults. [ABSTRACT FROM AUTHOR]

Delineating and mapping alteration zones in porphyry copper exploration is of special importance. In this study, satellite image processing techniques were employed to highlight alteration zones in the Zafarghand exploration area. The Zafarghand area is located in the southeastern part of Ardestan and the northwestern part of Isfahan. It is situated within the geological structural zones of central Iran and the intermediate magmatic arc of Urmia-Dokhtar. Various alteration haloes are present in this area, including phyllic, potassic, propylitic, argillic, and slightly siliceous alterations. In this study, the detection of related alterations was carried out using ASTER sensor imagery. Accordingly, considering the raster nature and digital form of satellite images, the digital number values of each pixel from the image matrices were considered as samples in a systematic network. Finally, the U spatial statistic algorithm was implemented as a moving window algorithm for determining anomaly samples in the set of digital number (DN) values of ASTER satellite image pixels. The results of this technique show that the application of the U-statistic method, considering its structural nature and neighboring samples in decision-making, has been successful and has proven to be very effective in determining the alteration zones in the Zafarghand area. It could be observed the delineated propylitic alteration by the U-statistic method is closely associated with the defined zone of propylitic alteration, which is also consistent with the field and microscopic observation of the porphyry Cu mineralization in this alteration zone. It is also observed that the determined phyllic alteration by this image processing is spatially conformable with the sericitic alteration presented in the alteration map (based on field observations and geochemical sampling). [ABSTRACT FROM AUTHOR]

Digital elevation models (DEMs) are crucial for numerous assessments of the Earth's surface, so this research aim to evaluate the quality of several open source DEMs like advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTM DEM), SENTINEL-1, and TerraSAR-X for digital elevation measurement (TanDEM-X). TanDEM-X is one of the newest DEM models; however, ASTER and SRTM are still the most used. To evaluate the qualities of these DEMs, the vertical accuracies of ASTER, STRM (all 30 m), SRTM, TanDEM-X (90 m), and SENTINEL 1 (range from 5 to 12.5 m) were tested using GPS reference points and The RMSE gave the values of ± 3.56 m ± 57.68 m, ±5.89 m, ±10.21 m and ± 20.25 m for used SRTM1, SENTINEL-1, SRTM3, TanDEM-X, and ASTER DEMs respectively. As is well known, obtaining a high-quality DEM is exceedingly challenging since it is time-consuming, expensive, and often constrained, therefore this study examined how to enhance SRTM1 as it gave the best result and assessed the effects of increasing the number of points on digital elevation model accuracy by using raster calculator and merge model in ArcGIS. The results showed that the merge model method gave the best result and, by increasing the number of reference points, the accuracy increased. The DEM produced by the enhanced SRTM (iSRTM) demonstrated noticeably better outcomes than the baseline SRTM DEM, with around 3.56 m RMSE. In this research, STRM-1 DEM is used to determine watershed basin delineation. The topographic map showed significant variations in the level of the Earth's surface, as the heights of the area ranged between 20 m and 120 m. The number of watersheds extracted in the Benban is 132 with different areas, the large area is about 72.14 km 2 , while the small area is about 1.13 km 2 , and between those areas, there are various areas. The largest recorded watershed circumference reached 48.94 km in area (72.14 km 2), while the lowest recorded perimeter is 5.40 km for the area (1.13 km 2). [ABSTRACT FROM AUTHOR]

This study evaluates the potential for mineral prospectivity mapping (MPM) within the Kerkesha area, southwestern Eritrea, using remote sensing and geochemical data analysis. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data were used for mapping zones of hydrothermal alteration, while assessment of geologic structures was based on automated extraction of lineaments from a digital elevation model (DEM). Integration of these alteration and structural datasets with surface geochemical data was carried out to identify pathfinder elements associated with Au–Cu–Zn mineralization as well as to evaluate and delineate anomalous regions in this relatively underexplored region of the Arabia Nubia Shield (ANS). Specifically, the modeling approach for the extraction and interpretation of mineralization-related spectral footprints was the selective principal component analysis (SPCA), and the lineament features extracted from DEM derivatives were integrated with the soil geochemical data and modeled by principal component analysis (PCA). The results revealed a NE–SW trend of lineaments, delineated zones of hydrothermal alteration indicating the presence of multi-deposit type mineralization, and identified pathfinder elements. In addition, Au–Cu–Zn anomalous zones were extracted by one-class support vector machine (OCSVM) and the performance of such classification was validated by the area under the curve (AUC) and the Youden index computed from receiver operating characteristic (ROC) curves and the Kruskal–Wallis test. The results showed significance in differences between the anomalous and non-anomalous zones and existence of a relationship between known mineral deposits and predicted anomalies. The proposed MPM shows promising results for robust automated delineation and understanding of mineralization processes. [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.

Bhutan's scholarly traditional medical system is called Bhutanese Sowa Rigpa medicine (BSM). It was integrated with the modern healthcare system in 1967. Over 200 medicinal plants are used to produce more than 100 poly-ingredient medicinal formulations. Although BSM is supported by well-documented principles, pharmacopoeias, diagnostic procedures, treatment regimens, and traditional quality assurance systems, modern quality control parameters have become essential to distinguish closely related species and prevent contamination from exogenous impurities. This study aims to establish reliable analytical methods and quality control parameters for Aster flaccidus Bunge and Aster diplostephioides (DC.) Benth. ex C.B. Clarke used as ingredients in the BMS poly-ingredient medicinal formulations. Furthermore, their reported phytochemicals and biological activities are also discussed in this study. Standard pharmacognostic techniques, including macroscopical and microscopical examinations of crude drugs, were employed to establish the quality control parameters for two Aster species. The physicochemical limits were determined as per the World Health Organization (WHO)-recommended guidelines and methods described in the Thai herbal pharmacopoeia. A high-performance thin-layer liquid chromatography (HPTLC) was used to develop a comparative chromatogram/phytochemical fingerprint for the crude extracts obtained from two Aster species. A literature review was conducted to record their isolated phytochemicals and biological activities. Two Aster species possess macro- and microscopic features such as colour, appearance, and shape. Physicochemical analysis of crude drugs from two Aster species including HPTLC fingerprinting of their methanol crude extracts also yielded adequate data to differentiate and confirm two Aster species before adding them to the BSM poly-ingredient medicinal formulations. From the literature review, only A. flaccidus was found to be studied for its phytochemical constituents, whereby 11 pure compounds were isolated from aerial parts and roots. The current study revealed distinct species-specific distinguishing features, including ecological adaptation, micromorphology, anatomy, physicochemical values, HPTLC chromatograms. These parameters can be used to authenticate the species identity and prevent adulterations, thereby improving the quality and safety of BSM formulations.