Airborne Gamma-ray Spectrometry Research Articles

A multi-disciplinary approach for uranium exploration using remote sensing and airborne gamma-ray spectrometry data in the Gebel Duwi area, Central Eastern Desert, Egypt

Uranium exploration plays a pivotal role in meeting global energy demands and advancing nuclear technology. This study presents a comprehensive approach to uranium exploration in the Gebel Duwi area of the Central Eastern Desert of Egypt, utilizing remote sensing and airborne gamma-ray spectrometric data. Multispectral remote sensing techniques, including Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Band Ratioing (BR), are employed to identify lithological units and hydrothermal alteration zones associated with uranium deposition, such as iron oxides, argillic, propylitic, and phyllic alterations. Additionally, airborne gamma-ray spectrometry data provide insights into the spatial distribution of radioelements, including uranium (eU), thorium (eTh), and potassium (K), as well as radioelement ratios (eU/eTh, eU/K, and eTh/K). The uranium migration index map (eU-(eTh/3.5)) and the F-parameter map (K*(eU/eTh)) have been generated to investigate the movement of uranium within various geological zones and characterize anomalous uranium concentrations. Statistical analyses, including mean (X), standard deviation (S), and coefficient of variability (C.V.), are conducted to identify uranium-rich zones. The integration of these datasets enables the generation of a uranium potential map highlighting areas of elevated concentrations indicative of uranium mineralization. Field observations and mineralogical analyses of collected samples validate our findings, confirming the presence of minerals associated with uranium mineralization in mapped high-potential areas. The significance of minerals like Fe-Chlorite, Fe-Mg-Chlorite, ferrihydrite, goethite, calcite, muscovite, dolomite, actinolite, vermiculite, and gypsum in indicating potential uranium mineralization processes underscores the importance of our results.

Application of airborne gamma-ray spectrometry in geological lithology mapping—a case study of a region in the Qinling Mountains, China

Application of airborne gamma-ray spectrometry in geological lithology mapping—a case study of a region in the Qinling Mountains, China

Biological assessment and radiological impact in Keana, North Central Nigeria: environmental implication and metabolites production.

The objective of the research was to examine microbial characteristics, metabolites produced, and the potential radiological risks present in mining soils located in Keana, North Central Nigeria. Soil samples were collected from various locations within Keana, Nasarawa State. Bacterial isolation was carried out, and molecular techniques were employed to characterize the bacteria found in the collected soil samples. Additionally, the susceptibility of these isolates to antibiotics was determined, and the bacteria screened for their ability to produce metabolites. The isolated bacteria were classified into three groups: Actinobacteria, Firmicutes, and Proteobacteria. The analysis of the spectra revealed that 1595 compounds were produced, including carboxylic acids, nitro compounds, aldehydes, anhydrides, esters, ketones, amides, phenols, alcohols, alkanes, alkenes, alkynes, and arenes. Some of the metabolites produced were oleic acid, 1,3-dioxolane, linoelaidic acid and oleic acid, 1-nonadecene, butylated hydroxytoluene, diisooctyl phthalate, bis(2-ethylhexyl) phthalate among others, and 1,2-benzenedicarboxylic acid (85.32%) as the most produced metabolite. Among the antibiotics tested, levofloxacin and ciprofloxacin exhibited the strongest antibacterial properties against the isolates. Airborne gamma-ray spectrometry analysis identified elevated levels of potassium, thorium, and uranium in the soils, indicating potential environmental hazards. However, no significant correlation was found between the presence of bacteria and radioactive elements. These findings emphasize the importance of comprehensive environmental monitoring in Keana to address potential health risks associated with microbial contamination and radioactive materials. Additionally, the study highlighted the role of microbial diversity in Keana soils in promoting the production of secondary metabolites with potential applications in pharmaceutical and industrial sectors..

Integrative mapping of radioactive and alteration zones in Um Had plutons, Egypt: Using Landsat 9, ASTER imagery, and airborne geophysical data

The study aims to assess the effectiveness of using ASTER, Landsat 9, and airborne geophysical data to generate maps depicting hydrothermally altered regions and their correlation with radioactive-mineralized zones in Egypt's Um Had area. Various image processing methods were applied, including color composite images, band ratios, selective principal component analyses, and lineament extraction with enhancement procedures. The ASTER ratios identified the three types of hydrothermal alterations; phyllic, argillic, and propylitic, with other significant alteration zones related to mineralization. Airborne gamma-ray spectrometry contour maps displayed marked varied levels of total count (T.C), eU, eTh, and K, ranging from 1.2 to 21.2 Ur, 0.5–12.34 ppm, 1.45–28 ppm, and 0.13–3.65 %, respectively. The highest anomalies of these radioelements concentration have coincided with the alkali feldspar granite and along their intrusive contact zone with the Hammamat Group sedimentary rocks. Higher anomalies are well recorded in the center and eastern regions of Um Had's, according to the radioelements composite image. The lowest concentrations of these radioelements are associated with gneiss, ophiolitic mélange, metavolcanic, Hammamat Group sedimentary rocks, Taref Formation, and Wadi sediments. To mitigate local magnetic effects, the total aeromagnetic data was reduced to the north magnetic pole (RTP). Power spectrum analysis of the RTP data identified distinct magnetic wavelengths for regional-residual components. In order to identify near-surface magnetic lineaments, such as contacts, shear zones, faults, and dykes, advanced algorithms were applied to the RTP data. The lineaments derived from ASTER and airborne magnetic data revealed dominant fault systems characterized by E–W, NE, NNW, NW and N–S trends, governing the structural framework of the study area. Depth levels of geological contacts and faults that represented pathways for altered and mineralized zones reached more than 1200 m (Euler deconvolution). These findings highlight the consistent results obtained when combining ASTER data with airborne survey data, allowing for the identification of hydrothermally altered zones and primary conductive zones.

A deep neural network for predicting soil texture using airborne radiometric data

The ternary nature of soil texture, defined by its proportions of clay, silt, and sand, makes it challenging to predict through linear regression models from other soil attributes and auxiliary variables. The most promising results in this field have been recently achieved by Machine Learning methods which are able to derive non-linear, non-site-specific models to predict soil texture. In this paper we present a method of constructing a pair of Deep Neural Network (DNN) algorithms that can predict clay and sand soil contents from Airborne Gamma Ray Spectrometry data of K and Th ground abundances.We tested the algorithm's hyperparameters through various configurations to optimize the DNNs' performance, effectively avoiding underfitting and overfitting of the models. This led to the creation of a high-resolution 20 m × 20 m soil texture map from dense AGRS data, significantly refining the previous map's granularity. The application of the obtained DNN models to unseen sites can be supported by future training on additional textural classes.

Inference of minerals at Redondão kimberlite crater, Parnaíba Basin, Brazil, based on interpretation of airborne gamma-ray spectrometry and ASTER data

Inference of minerals at Redondão kimberlite crater, Parnaíba Basin, Brazil, based on interpretation of airborne gamma-ray spectrometry and ASTER data

Mapping bauxite-associated alterations in the Boke region (NW part of Republic of Guinea), using the airborne gamma-ray spectrometry data

Mapping of highly altered zones favorable to mineralization is crucial to finding useful mineral deposits. However, several methods have been used to locate areas subject to weathering processes, including analysis of airborne gamma-ray spectrometry data, which have demonstrated accurate and reliable results. In order to target other promising areas, and ensure the sustainability of bauxite mining, gamma-ray spectrometry was carried out and applied for the first time in the Boke region, located in the north–west of the Republic of Guinea which encompassing the world's famous bauxite district. The results obtained from the K/eU, K/eTh ratios, the F parameter and the potassium map were processed by the fuzzy logic model using ArcGIS software, the model can be used to merge the resulting informative maps into a single mineral prospectivity map, serving as a guide for mineral exploration. Three zones of high mineral prospectivity have been identified, essentially the Ordovician formations at Pita, the Silurian at Telimele and the Devonian at Faro. According to these preliminary prospecting results, the delineated areas contain localities that are probably potential, giving the green light for more advanced prospecting.

Lithological discrimination of the Fawakhir-Atalla belt in the Central Eastern Desert of Egypt based on Landsat-9 remote sensing data, airborne gamma-ray spectrometry, field and petrographic investigations with implications on the evolution of the Arabian Nubian Shield

The Central Eastern Desert (CED) is a key territory for understanding the evolution of the Arabian Nubian Shield (ANS) in Egypt as it contains Cryogenian-Tonian ensimatic supracrustal assemblages, such as ophiolitic and arc volcanic rocks, as well as gold deposits. So, it has been the subject of extensive studies over the last two decades. However, the lithological mapping of the Fawakhir-Atalla belt, located west of the Meatiq gneiss dome (infrastructure) of the CED, is still debated, as the magmatic texture of some rocks was partially obscured owing to the shearing and alteration related to the Najd Fault System, mantle CO2-bearing fluid, and igneous activity in the final stage of the Pan-African Orogeny. In this regard, integrated studies of airborne gamma-ray spectrometry and Landsat-9 satellite imagery processing techniques, as well as field and petrographic investigations, have been used for the lithological mapping of the belt. The results led to the following sequence; ophiolitic rocks > island arc assemblages > older granitoids (syn-tectonic subduction-related) > Hammamat Group (molasse-type origin) > post-Hammamat felsite > younger granite (post-tectonic suture-related). The applied color composite images, selective band ratios, and image transformation techniques show a clear distinction between rock units. Older granitoids are tonalite to quartz diorite, while younger granites are monzo-to syenogranite. They are well-discriminated from each other using band ratios, and younger granites have the highest K, eU, and eTh values coherent with the post-Hammamat felsite. The image enhancement and image transformation techniques show a clear discrepancy between the mélange rocks and Hammamat conglomerates. Mélange rocks are composed of fragments embedded in a foliated matrix, while Hammamat conglomerates are grain-supported with pebbles of volcanic source and have higher K, eU, and eTh values. Volcanic rocks in the belt are not a part of the Dokhan series as they are metamorphosed with a composition range from meta-basalts to meta-rhyolite, and show mainly aphanitic to infrequently porphyritic textures, which are typical of island arc metavolcanics.

Radiometric characteristics of some metallic ores and nonmetallic deposits: an example, Wadi Al-Allaqi, South Eastern Desert, Egypt

Hydrothermal alteration processes are connected to many mineral formations, particularly auriferous deposits. In this study, airborne gamma-ray spectrometry (GRS) data and the analysis of radioactive materials (eU, eTh, and K) are applied to search for regions with hydrothermal alteration activity. An example is presented from Wadi Al-Allaqi, South Eastern Desert, Egypt. GRS was used to analyse various radiometric data to address potential mineral deposit areas, to map regions potentially showing metallic ore mineralisation, and to point out new geological mineral resources. The Kd (potassium deviation), “F” parameter and Th-normalisation of the K and eU anomalies were calculated, and locating new exploratory targets in the study area that exhibit high F-parameter, Kd, and K/eTh values was recommended. Additionally, the research region has a few isolated enriched spots of (K). Therefore, GRS data was used to characterise and estimate potential metallic ores, nonmetallic deposits, and gold ore zones associated with the alteration zones. Results show that most of the known mineral deposits and gold occurrences in the area, according to the metallogenic map of Egypt, are located in zones with a ratio value of (0.25–0.30) (K%/(U or Th ppm)) maps which may suggest a moderate degree of alteration. Also, most mineral deposits and gold occurrences are found in intermediate altered zones, or K-enriched sites, with a Kd% of (0.2. The work represents an attempt to map hydrothermal alteration zones associated with mineral deposits in the Wadi Al-Allaqi area. Generally, natural radiation characteristics and attributes suggest criteria that can be used globally for regional mineral exploration.

Application of High-Resolution Aeromagnetic and Gamma-ray Spectrometry Surveys for Litho-Structural Mapping in Southwest China

Airborne geophysical surveys serve as an effective tool for litho-structural mapping, providing extensive and high-resolution underground information. They offer vital data support for the interpretation and analysis of lithologies and structures, complementing surface geological mapping. In the study area of the Nanpanjiang-Youjiang metallogenic belt in southeast China, we obtained high-resolution aeromagnetic and gamma-ray spectrometry data covering an area of approximately 27,000 km2, which facilitated the conduct of litho-structural mapping. The total magnetic intensity, reduction to the pole, and directional derivative maps generated from the aeromagnetic data, efficiently identified concealed rocks and faults. Additionally, the total count, potassium, thorium to potassium ratio, and ternary maps generated from the airborne gamma-ray spectrometry data demonstrated advantages in distinguishing carbonate rocks from clastic rocks. They also provided more comprehensive geological information, refining the structural strike and location interpreted by the aeromagnetic data. The litho-structural map produced in this study significantly contributes to our understanding of the structures in the Nanpanjiang area and offers valuable guidance for successful mineral exploration endeavors.

Predicted resource assessment of Central Kazakhsta ore districts based on airborne geophysical methods

Purpose. The research is aimed at creating a high-quality geophysical basis for the additional geological study of Central Kazakhstan in determining the geological structure of the study area, identifying promising areas for further geological exploration, as well as analyzing the anomalous distribution of various minerals. Methodology. The research uses the methods of aeromagnetic, airborne gamma-ray spectrometry and gravimetric (ground) surveys. The obtained new airborne geophysical data are used for additional study of the geological structure of the district and the creation of a model of the geological structure of the study area. Gamma-ray spectrometry data analysis is conducted for detailed mapping of intrusive complexes and study of their lithological heterogeneity. Findings. The processing and interpretation of the materials of the conducted field studies in combination with the results of the geological-geophysical data analysis made it possible to refine the geological structure and to present a model of ore-prospecting complexes in the study area. Areas with an anomalous distribution of potassium, uranium, and thorium have been identified, which make it possible to assess the structural heterogeneity of hidden magmatic massifs and to reveal a connection with gold, copper-polymetallic and rare-metal mineralization. Recommendations for further detailed geological exploration, including prospecting-exploration drilling, are given. Originality. Research has shown the high efficiency of airborne geophysical methods, such as aeromagnetic and airborne gamma-ray spectrometry surveys to study the geological structure of ore areas, and in combination with detailed gravimetric exploration to identify lithological heterogeneity of igneous and sedimentary rocks in the study area. New scientific-methodological techniques and the geological structure model based on them gave an opportunity to assess the prospect of the study area for ore mineralization. Practical value. The identified promising areas for mining of minerals are of interest for further research and exploration. The integrated use of geological-geophysical data will make it possible to determine more precisely the nature of radioactive anomalies and to reveal their relationship with ore-prospecting horizons. In general, the research results contribute to increasing the efficiency and reducing the geological survey costs.

Digital mapping of soil classes in Southeast Brazil: environmental covariate selection, accuracy, and uncertainty

DSM has been used to meet the demand for soil information over large areas in more detailed resolution consuming less time. Soil-forming factors proxies (environmental covariates) are crucial to increase accuracy and provide new insights about the soil-landscape. DSM of the southern region of Minas Gerais state (52,982 km2) was generated. Soil profiles that comprise the legacy of decades of pedological surveys were gathered and associated with new (paleoclimatic, organic carbon, and airborne gamma-ray spectrometry) or less explored (digital terrain and climatic variables) environmental covariates under tropical conditions. An iterative routine of soil modeling, accuracy, uncertainty (entropy and MESS) assessment, and discussions concerning soil legacy was performed to equate pattern recognition with knowledge discovery from the random forest algorithm. The soil map was generated with 89% accuracy. The probability maps of the occurrence of the soil classes allowed soil-landscape insights. Less than 0.5% of the areas showed negative MESS, indicating an adequate representation of the soil samples concerning the environmental covariates. The most important environmental covariates were geophysical airborne gamma-ray spectrometry (K and eTh), distance from drainage channels, and paleoclimate (precipitation estimated from 22,000 years ago) consistent with the polygenetic soils.

Decomposing and recovering airborne radiometric data through principal component analysis applied on flight-line data: An alternative to reduce noise

Airborne gamma-ray spectrometry (AGRS) data provide valuable information about the distribution of radiometric elements on earth’s surface. However, the presence of noise can hinder the interpretation or the identification of subtle variations of radioelement concentrations that can be economically attractive. Previous research has demonstrated that techniques based on matrix factorization, such as noise-adjusted singular value decomposition (NASDV) and minima noise fraction (MNF), can reduce noise when applied to AGRS raw spectra. Nevertheless, the raw spectra often are unavailable for end users, limiting the widespread adoption of such techniques. In this context, we use principal component analysis with the flight-line data before interpolating the data onto a regular grid as a means to reduce noise when the raw spectra are no longer available. We use our approach on two AGRS data sets located in Brazil and one in the United States. For Brazil’s AGRS data, results indicate that noise can be attenuated through eigendecomposition projection and recovery of the radiometric variables. Furthermore, our technique can highlight some geologic features dependent on the number of eigenvectors used to reconstruct the database. For the U.S. AGRS data set previously filtered with NASDV, our methodology seems to produce only marginal improvement. Therefore, our methodology might be particularly successful for AGRS data whose acquisitions were conducted before NASDV and MNF were proposed as radiometric data processing techniques.

Clustering airborne gamma-ray spectrometry data in Nova Friburgo, State of Rio de Janeiro, southeastern Brazil

The goal of this study was to test different image clustering techniques, using airborne gamma-ray spectrometry data to optimize the interpretation of areas with similar properties in large scale. The methodology applied was based on the comparison of two techniques of data-driven classification (K-means and Gaussian Mixture Models) and a technique of knowledge-driven classification (Simplified RGB) to discriminate domains from the primary variables potassium (K), uranium (eU), and thorium (eTh) obtained from airborne gamma-ray spectrometry surveys. The performance of these three methods was evaluated through pre-processing techniques and post-processing including the best number of clusters/classes, visual interpretation, internal validation, and boxplot analysis. The clustering performance was considered satisfactory through the visual interpretation and comparison with the geological map and the DEM, for all three methods. For a quantitative analysis, the simplest model of unsupervised clustering Gaussian Mixture Models prevailed.

Using of airborne gamma-ray spectrometric data to the exposure of potassic alteration -recognition of alteration relates to gold mineralization

It is well known that many mineral deposits are related to hydrothermal processes, especially auriferous deposits. In this research paper, we show how to distinguish areas that have experienced hydrothermal activity, by construing airborne gamma-ray spectrometry data, especially potassium. An indirect application of aerial gamma-ray spectrometry technique is used to detect possible minerals deposits.In this region, an airborne gamma ray survey (K, eU and eTh) was carried out, based on irregular K, “F” parameter -, and Th-normalized of the K and eU anomalies. This work exhibits the mapping of hydrothermal regions possibly showing gold mineralization and the pointing out of new geological portions for this sequence, establishing prospective criteria for regional mineral exploration.We can suggest a new exploratory target, the area that is located next to Jabal Al-Ardiya (white colour on ternary map), which is characterized by high values of F-parameter, KD%, and K/eTh. Besides, enriched areas are found scattered in the north-eastern side of the study area. As result, the airborne gamma ray spectromertic data, might be used for estimation of prospective Gold Ore zones associated with the potassium alteration."

Airborne Radiometric Surveys and Machine Learning Algorithms for Revealing Soil Texture

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km2 agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

Mapping of favourable mining areas in the Tiouit area by multispectral remote sensing and airborne gamma-ray spectrometry coupled with geochemical data (Eastern Anti-Atlas, Morocco)

ABSTRACT The current investigation concern Tiouit region in order to perceive potential mining zones. Remote sensing data were the main component to process. In order to spot geochemical anomalies associated with the target zones, multispectral ASTER data, gamma-ray spectrometry, and stream sediment data were used. Crosta and SAM applications granted to map a spatial distribution of propylitic, phyllic, clay, and ferruginous alteration zones. The normalized ratios let the delineation of potassic alteration zones, including the Tiouit gold mine characterized by an intense alteration in the Ikniwn granodiorite. Thus, the potassic alteration zones are consistently co-located with the tectonic structures materialized by strong fracturing densities. The stream sediment geochemical investigation revealed that the cited areas have an important potential of mineralization, with high concentrations of As (136 g/t), Cu (91 g/t), Pb (141 g/t), Zn (392 g/t), Ag (3 g/t), Mo (11 g/t), Mn (0.2 g/t), and Fe (10.63 %).

Experimental and Simulated Spectral Gamma-Ray Response of a NaI(Tl) Scintillation Detector used in Airborne Gamma-Ray Spectrometry

Abstract. The objective of this work is to simulate the spectral gamma-ray response of NaI(Tl) scintillation detectors for airborne gamma-ray spectrometry (AGRS) using the state-of-the-art multi-purpose Monte Carlo code FLUKA. The study is based on a commercial airborne gamma-ray spectrometry detector system with four individual NaI(Tl) scintillation crystals and a total volume of 16.8 L. To validate the developed model, radiation measurements were conducted using 57Co, 60Co, 88Y, 109Cd, 133Ba, 137Cs and 152Eu calibration point sources with known activities and source-detector geometries under laboratory conditions. In addition, empirical calibration and resolution functions were derived from these measurements combined with additional radiation measurements adopting natural uranium, thorium and potassium volume sources. The simulation results show superior accuracy and precision compared to previous AGRS simulation models with a median relative spectral error < 10 % for most of the radiation sources. Moreover, the implementation of a lower level discriminator model and detailed modelling of the laboratory result in a significant improvement in model accuracy for spectral energies < 100 keV compared to previous studies. Yet thorough statistical analysis incorporating statistical and systematic uncertainty estimates revealed statistically significant deviations between the simulated and measured spectra in the spectral region around the Compton edge, which could be attributed to the scintillator non-proportionality. These findings imply that the linear energy deposition model applied in this and previously developed AGRS simulation models should be revised and considered to be replaced by more accurate non-proportional models.

Analysis of airborne magnetic and gamma-ray spectrometry data for the geothermal source and conduits of the Ikogosi warm spring, southwestern Nigeria

Analysis of airborne magnetic and gamma-ray spectrometry data for the geothermal source and conduits of the Ikogosi warm spring, southwestern Nigeria

Radiological, geochemical, and environmental assessment in Xuancheng, China: The airborne gamma-ray spectrometric view

Radionuclides in the environment have been considered a health risk for many years owing to their contribution to the radiation dose to the human body. A great deal of field survey research has been conducted in this area. However, few researchers have studied the key sources of geological and geochemical substances that pose radioactive environmental problems from the perspective of airborne gamma-ray spectrometry. This study aims to determine the radiation variations in geological units caused by rocks containing radionuclides, evaluate the level of radiation, and analyze as well as identify the key radio-elements. The content of 40K, 238U, 232Th, and the total count (TC) in 15 different geological units were studied based on the concentration data. The gamma absorbed dose rate (D) of the whole region was calculated to identify and evaluate the main areas of high radiation. The quantitative statistical methods, the Pearson correlation analysis, principal component analysis (PCA), hierarchical cluster analysis (HCA), and geochemical mapping were used to analyze the selected high radiation areas and reveal potential key lithological factors. The results indicate that the Cretaceous intrusive rock, in the northeast of the study area, is a major source of natural radionuclides and continuous radiation. The high radiation in this area is strongly associated with the Yaocun rock mass containing K-feldspar granite, and the correlation coefficient of the 232Th with effective dose was the highest (0.91), whereas that of 238U was the lowest (0.49). The study has determined that 232Th is the key radio-element, causing high radiation by comparing the results of HCA of field gamma-ray measurement data. The findings from this study are valuable for determining the key factors causing high radiation levels in similar exposure conditions.