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Environmental concern is a significant driver of demand for sustainable initiatives, emphasizing the significance of green finance in academic research. While sustainability issues attract increasing global focus, the need to map the development and thematic evolution of green finance becomes important. Therefore, the present study mounts the development and thematic evolution of green finance through a comprehensive bibliometric analysis. Using the Scopus database, we analyzed 887 articles to identify key trends, collaboration networks, and thematic clusters. It was found that China has made a significant contribution to academic literature and has had notable collaborations with South Asian institutions. The central themes are carbon emissions, green technology innovation, and renewable energy. The two advanced bibliometric tools, Biblioshiny and VOSviewer create thematic maps, co-citation networks, and keyword analyses to provide insights into the intellectual structure of green finance research. Based on this study, the most influential authors, major journals, and emerging research areas are pinpointed to offer a pathway for future research in this multidisciplinary domain. The study's findings underscore green finance's significant role in achieving sustainable development and promoting environmentally friendly initiatives. [ABSTRACT FROM AUTHOR]

The purpose of this study is to locate groundwater-saturated aquifers in the Vindhyan fringe belt in the Mirzapur district of Uttar Pradesh, India, and evaluate their protection using geoelectrical indices. The Schlumberger electrode layout, with a maximum half-current distance between electrodes of 300 m, was used to perform three gradient profilings and six geoelectrical soundings. The inversion IPI2win program and the traditional partial curve matching approach were used for geoelectrical sounding data interpretation. Four to five geologic units are identified in the research region based on the interpretation of the geoelectrical sounding data. These are the top-surface soil, clay, kankar/laterite and sand, weathered sandstone, and compact sandstone. The research region is characterized by HA-type sounding curves, and the obtained findings suggest the presence of groundwater-saturated zones and cracks in the area. The weathered sandstone saturated with water shows resistivity ranges between 375.4 and 407.1 Ω-m and depth ranges from 96.8 to 97.6 m. Thematic maps were prepared for total longitudinal conductance, transverse resistance, overburden thickness, and electrical anisotropy. The protective capacity of the aquifer is measured using the transverse resistance (Tr) and longitudinal conductance (Lc) of the Dar Zarrouk parameters. Based on the longitudinal conductance of the aquifers, the results obtained indicate that the research region is dominated by a good aquifer protective capacity rating. [ABSTRACT FROM AUTHOR]

Groundwater is the most dynamic natural resource that is not uniformly distributed both in space and time. Identifying it for sustainable water resource development for domestic use, irrigation, and industrial purposes is the biggest challenge and key concern due to climate change, overexploitation, and a lack of proper management. Geographical information system (GIS) and remote sensing (RS) play a fundamental role in identifying suitable groundwater potential and recharge zones. In this study, groundwater potential and recharge zone map are delineated using GIS and RS techniques integrated with Analytic Hierarchy Process (AHP) for the Melka Kunture Watershed in Ethiopia. The thematic layers used were: Lithology, geomorphology, slope, lineament density, land use/cover, rainfall, drainage density and soil. GIS has been used to integrate and overlay thematic layers using a weighted overlay analysis tool, whereas the AHP method has been used to assign the weights, normalize, and rank thematic layers and their associated sub-themes based on their suitability, characteristics, or influence on groundwater potential and recharge zones. The output groundwater potential zone map is categorized into four suitable zones: high potential cover 1105.60 km2 (25.70%), moderate potential 2308.00 km2 (53.73%), low potential 880.0 km2 (20.49%), and very low potential 47.80 km2 (1.10%), whereas there are three suitable groundwater recharge potential zones: high potential cover 250.20 km2 (5.80%), moderate recharge 3647.90 km2 (84.00%), and low recharge 443.50 km2 (10.20%) of the study area. Hence, the study areas have been more suitable for groundwater potential and recharge zones as compared to the total area. The groundwater potential map was validated using the existing water source and well points, and it indicated a good prediction accuracy of 88%. Thus, the delineated groundwater potential and recharge zone maps are reliable, and the resultant potentiality mapping has played a vital role in the sustainable development and management of the water resources in the study area. Highlights: → The integration of GIS and RS techniques with the MCDA-AHP method is a powerful tool for delineating the groundwater potential and recharges zones in the Melka Kunture Watershed. → Utilizing both recent conventional data and high-resolution satellite imagery is crucial for creating accurate thematic layers and maps of groundwater potential and recharge zones. → To further validate and enhance these techniques, conducting well drilling or pump tests using geophysical investigations is recommended to gain a more detailed understanding of groundwater potential and recharge zones, as well as to estimate yields. [ABSTRACT FROM AUTHOR]

Currently, global warming, invasive alien species and tourism development pose major threats to Natural World Heritage sites, and the strengthening of conservation methods and management programs in buffer zones is urgent for the sustainable development of sites. Agroforestry, as a nature-based solution, not only promotes the buffer zone to effectively maintain the Outstanding Universal Value of the heritage site, but also balances the relationship between the conservation of the heritage site and the economic development of the buffer zone, and effectively enhances the protection of the buffer zone in response to various threats. However, there is currently a lack of comprehensive understanding of research trends, research focuses, and recent developments, regarding the conservation of natural heritage sites and buffer zone agroforestry development. Therefore, this study utilized the Scopus database along with Excel and Bibliometrix software to conduct a bibliometric analysis and explore and visualize popular research topics and foreword issues related to Natural World Heritage conservation and buffer zone agroforestry development. We discuss the current publication trends and quantity, keyword and abstract word frequencies, thematic maps and evolutions, journal productivity, national publication outputs, collaboration relationships, and contributing institutions. The research shows that the relationship between biodiversity conservation and agroforestry has been the focus of research in the field since 1992, and the development of agroforestry has contributed to biodiversity conservation in heritage sites. However, there have been fewer studies addressing the geomorphic and aesthetic value of agroforestry conservation, and little attention has been paid to buffer zone development. Based on this, this manuscript suggests that in the future, emphasis should be placed on the linkage between the development of buffer zones and heritage conservation, especially in the Karst World Heritage Sites with ecologically fragile, and that the role of agroforestry development in buffer zones should be strengthened in the promotion of ecological balance and sustainable development of the sites, to provide scientific references for the conservation and development of other geoheritage sites around the globe. [ABSTRACT FROM AUTHOR]

Tropical cyclone causes large-scale devastation and destruction in the coastal plains of India, particularly in Odisha, which is the most cyclone-affected state in the country. Tropical cyclones are projected to be more powerful and widespread due to changing climate. Hence, the risk assessment of tropical cyclone is necessary to identify cyclone-risk areas in coastal Odisha which may help in the mitigation of the damages caused by cyclones. Therefore, this study utilizes geospatial techniques to produce a comprehensive risk map posed by tropical cyclones and to estimate the degree of risk for coastal districts of Odisha. For this, we evaluated the district-level cyclone risk for coastal Odisha using multi-criteria decision-making (MCDM) technique by considering 21 parameters for each of the four components of risk, i.e., exposure, hazard, vulnerability, as well as mitigation capacity. For each criterion, thematic raster map layers were created and weighted using a fuzzy analytical hierarchy process (FAHP). We prepared individual risk component maps using weighted overlay techniques and finally integrated all indices to create the risk map. The study shows that 13% area of the study area comes under a very high-risk zone whereas, 25% area comes under a high-risk zone. The central (Cuttack, northern parts of Khordha, and south-western parts of Jajpur district) and the eastern part (most of the parts of Jagatsinghpur, Kendrapara, and northern parts of Puri district) of the study area come under high to very high tropical cyclone impact zone. Almost 67% of the total area is highly vulnerable to tropical cyclones and mainly concentrated near the shoreline. The applied approach and results can assist the local authorities in identifying vulnerable and hazardous locations and developing workable solutions for the mitigation of revised cyclone threats in the coastal districts of Odisha. [ABSTRACT FROM AUTHOR]

The process of determining whether a specific portion of land is suitable for a specific purpose is known as land suitability analysis (LSA). In order to promote sustainable development in semi-arid regions, the objective of this study is to analyse, evaluate, and identify the land for green growth based on topography, climate, and soil characteristics. Twelve thematic maps are prepared by using remote sensing satellite data. The Landsat 8 OLI/TIRS is used for the preparation of the thematic maps like land use land cover (LULC), normalized difference vegetation index (NDVI), top soil grain size index (TGSI), and geomorphology (GM), and DEM data is used for the preparation slope, and drainage density (DD). The collateral data is used to prepare geology and soil thematic maps. From the field work, we have collected soil samples for the compulsory physicochemical parameters such as soil EC and soil N-P-K which were taken into consideration and prepared thematic maps. The analytical hierarchy process (AHP) was used to generate the LSA of the research region, by assigning the appropriate weights to each criterion and sub-criterion for the thematic maps. Geographic information systems (GIS) and the multicriteria decision-making (MCDM) approach were used in the study's methodology. The LSA of the study area has been categories in to four types, i.e., highly suitable, moderately suitable, marginally suitable, and not suitable. The results revealed that 421.31 sq.km (40.09%) is not suitable for agriculture green growth in the study region, whereas 89.58 sq.km (8.52%) is moderately suitable, 267.66 sq.km (25.47%) is marginally suitable, and 266.54 sq.km (25.36%) is highly suitable. Accuracy assessment has validated the LSA map's accuracy (AA). The AA of LSA is 84.22%, which demonstrates a strong connection with the actual data. The research's results could be helpful in locating productive agricultural areas in various parts of the world. The decision-making AHP tool paired with GIS provides a novel method. [ABSTRACT FROM AUTHOR]

Soil erosion inventory of a river basin is vital for effective soil conservation and sustainable development considering the ongoing Global change. In the current study, gross soil erosion rates (A) are estimated for a mountainous river in a tropical climate, the Karamana River Basin (KRB), southern India by utilizing the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model computes 'A', as a product function of five variables; rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and erosion control practice factor (P). To compute these five parameters, the digital elevation model, slope, normalized vegetation index (NDVI), rainfall and land use/land cover (LULC) are used along with the texture data of soil samples collected from KRB. The estimated A values range between 0 to 738.44 t ha−1 year−1, with an average of 10.22 t ha−1 year−1 whereas the sediment yield (SY) estimated by utilizing the sediment delivery ratio (SDR) model ranges between 0 to 246.68 t ha−1 year−1 with an average of 1.58 t ha−1 year−1 for KRB. For further validation, a soil erosion potential index (SEPI) map is developed to identify the soil erosion-prone zones of KRB using the geo-environmental thematic maps following the analytic hierarchy process (AHP). Finally, rainfall impacts on soil erosion are evaluated and quantified for KRB, considering the recent marked variations in rainfall that are induced by the extreme climatic events (cyclones/high rainfall/floods) along the West coast of India. The outcome of this study suggests that increasing rainfall by one standard deviation of the long-term average causes a significant increase in low and medium soil erosion regions. [ABSTRACT FROM AUTHOR]

Several investigations have evaluated the research trajectory concerning entrepreneurship; nonetheless, only a few studies have examined the literature trajectory regarding entrepreneurship in tourism. Therefore, this research explores papers spanning from 2013 to 2023, mapping thematic, intellectual, and conceptual frameworks using bibliometric techniques. The research delves into scientific output, prolific authors, influential articles, co-occurrence of keywords, co-citations, and many others. The keywords "tourism" OR "travel & tourism" AND "entrepreneurship" OR "entrepreneur" were strategically employed to encompass 514 articles and review papers published in English between 2013 and 2023. VOSviewer was used as a technique for doing topic grouping alongside performance analysis. With 85 articles, 2023 is the most productive year. The most influential institution is "The Hong Kong Polytechnic University" and the nation is the United Kingdom correspondingly. Likewise, the most renowned journal is "Tourism management," and the most productive journal is "journal of sustainable tourism". Furthermore, the most cited article is "Scale, change and resilience in community tourism planning." This research provides researchers with insights into the existing state of research on entrepreneurship in tourism and offers guidance for future research. This study is the inaugural endeavor to present both performance evaluations and scientific clusters of the literature on entrepreneurship in tourism. [ABSTRACT FROM AUTHOR]

The management of groundwater systems is essential for nations that rely on groundwater as the principal source of communal water supply (e.g., Mohmand District of Pakistan). The work employed Remote Sensing and GIS datasets to ascertain the groundwater recharge zones (GWRZ) in the Mohmand District of Pakistan. Subsequently, a sensitivity analysis was conducted to examine the impact of geology and hydrologic factors on the variability of the GWRZ. The GWRZ was determined by employing weighted overlay analysis on thematic maps derived from datasets about drainage density, slope, geology, rainfall, lineament density, land use/land cover, and soil types. The use of multi-criteria decision analysis (MCDA) involves the utilization of the multi-influencing factor (MIF) and analytical hierarchy procedure (AHP) to allocate weights to the selected influencing factors. The MIF data found that very high groundwater recharge spanned 1.20%, high zones covered 40.44%, moderate zones covered 50.81%, and low zones covered 7.54%. In comparison, the AHP technique results suggest that 1.81% of the whole area is very high, 33.26 is high, 55.01% is moderate, and 9.92% has low groundwater potential. The geospatial-assisted multi-influencing factor approach helps increase conceptual knowledge of groundwater resources and evaluate possible groundwater zones. [ABSTRACT FROM AUTHOR]

This study aims to examine, ascertain, and measure the extent of research conducted on real-time surveillance video analytics (RTSVA) and uncover the patterns, advancements, and progression in the SCOPUS database. An electronic search methodology was employed to identify the most relevant scholarly papers. Each analytical tool was analyzed using the R program code and VOS Viewer software. Multiple factors were explored, including co-authorship, co-citation, conceptual structure, co-word occurrence, trend themes analysis, thematic map, and visualization analysis. It is observed the study includes data from 653 sources, such as journals, books, and conference proceedings. There are 1041 documents, with an annual growth rate of 21%. IEEE Access has the highest impact, and Multimedia Tools and Applications has the second highest source impact. The most significant author among the research group is Chen Y, with a fractionalization value of 6.59 (27 articles), followed by Wang J (15 articles) with a value of 3.80. The keywords related to the video analytics domain along with its frequency of occurrence, are "Edge computing," which has appeared 158 times, and video surveillance has appeared 95 times. The Thematic map is divided into four quadrants: Niche, Motors, Emerging, and Basic themes. Traffic surveillance, blockchain, and COVID-19 are under Niche themes. It is also necessary to explore the sociological and ethical implications linked to using video surveillance systems. This study has the potential to aid both novice and experienced researchers in identifying novel research domains, suitable sources, and opportunities for collaboration. The results pertaining to relational and evaluate methodologies could be helpful to the new researchers. [ABSTRACT FROM AUTHOR]

Objective: To conduct a bibliometric analysis of the prospects and obstacles associated with dual- and multi-energy CT in thoracic disease, emphasizing its current standing, advantages, and areas requiring attention. Methods: The Web of Science Core Collection was queried for relevant publications in dual- and multi-energy CT and thoracic applications without a limit on publication date or language. The Bibliometrix packages, VOSviewer, and CiteSpace were used for data analysis. Bibliometric techniques utilized were co-authorship analyses, trend topics, thematic map analyses, thematic evolution analyses, source's production over time, corresponding author's countries, and a treemap of authors' keywords. Results: A total of 1992 publications and 7200 authors from 313 different sources were examined in this study. The first available document was published in November 1982, and the most cited article was cited 1200 times. Siemens AG in Germany emerged as the most prominent author affiliation, with a total of 221 published articles. The most represented scientific journals were the "European Radiology" (181 articles, h-index = 46), followed by the "European Journal of Radiology" (148 articles, h-index = 34). Most of the papers were from Germany, the USA, or China. Both the keyword and topic analyses showed the history of dual- and multi-energy CT and the evolution of its application hotspots in the chest. Conclusion: Our study illustrates the latest advances in dual- and multi-energy CT and its increasingly prominent applications in the chest, especially in lung parenchymal diseases and coronary artery diseases. Photon-counting CT and artificial intelligence will be the emerging hot technologies that continue to develop in the future. Critical relevance statement: This study aims to provide valuable insights into energy-based imaging in chest disease, validating the clinical application of multi-energy CT together with photon-counting CT and effectively increasing utilization in clinical practice. Key Points: Bibliometric analysis is fundamental to understanding the current and future state of dual- and multi-energy CT. Research trends and leading topics included coronary artery disease, pulmonary embolism, and radiation dose. All analyses indicate a growing interest in the use of energy-based imaging techniques for thoracic applications. [ABSTRACT FROM AUTHOR]

Assessing the spatial distribution of the erosion process is considered a critical initial step to provide valuable insights to decision-makers for devising an effective erosion mitigation strategy to reduce erosion damages. This research was conducted based on a revised universal soil loss equation (RUSLE) model integrated with the geographic information environment (GIS) within the Wadi El Ghareg watershed located in the Menzel Bourguiba region in northeastern Tunisia to simulate the spatial distribution of erosion across the basin which has been experiencing adverse effects of climate change, characterized by periods of drought and heavy rainfall. The RUSLE incorporates several variables, including rainfall erosivity (R), soil erodibility (K), cover management (C), slope length (LS), and conservation practices (P), serving as key predisposition parameters in this research. For the validation process of the applied model, 200 points were selected to create an inventory map; the points were selected based on satellite images and field surveys. The obtained thematic maps were normalized by fuzzy logic and overlaid using the model equation in the GIS. The results identified the most severely eroded areas requiring immediate erosion control measures. Hence, the results reveal that about 1.71% of the area is covered under severe erosion risk, 0.13% area under high erosion risk, 0.26% area under moderate erosion risk, 0.27% area under low erosion risk, and 97.63% of the area under very low erosion risk. The accuracy of the model was evaluated based on the receiver operating characteristic curves (ROC) and the areas under the curves (AUC). The result showed that this model had an excellent predictive accuracy for soil erosion susceptibility, with AUC values of 0.967. The final produced map will be used as a basis for suggesting a framework that can help make practical policy recommendations to fight against erosion in the context of sustainable management of the watershed. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance (IR) is considered the pathogenic driver of diabetes, and can lead to obesity, hypertension, coronary artery disease, metabolic syndrome, and other metabolic disorders. Accumulating evidence indicates that the connection between gut microbiota and IR. This bibliometric analysis aimed to summarize the knowledge structure of gut microbiota in IR. Methods: Articles and reviews related to gut microbiota in IR from 2013 to 2022 were retrieved from the Web of Science Core Collection (WoSCC), and the bibliometric analysis and visualization were performed by Microsoft Excel, Origin, R package (bibliometrix), Citespace, and VOSviewer. Results: A total of 4 749 publications from WoSCC were retrieved, including 3 050 articles and 1 699 reviews. The majority of publications were from China and USA. The University Copenhagen and Shanghai Jiao Tong University were the most active institutions. The journal of Nutrients published the most papers, while Nature was the top 1 co-cited journal, and the major area of these publications was molecular, biology, and immunology. Nieuwdorp M published the highest number of papers, and Cani PD had the highest co-citations. Keyword analysis showed that the most frequently occurring keywords were "gut microbiota", "insulin-resistance", "obesity", and "inflammation". Trend topics and thematic maps showed that serum metabolome and natural products, such as resveratrol, flavonoids were the research hotspots in this field. Conclusion: This bibliometric analysis summarised the hotspots, frontiers, pathogenesis, and treatment strategies, providing a clear and comprehensive profile of gut microbiota in IR. [ABSTRACT FROM AUTHOR]

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Background: This study aims to conduct a scientometric analysis and thematically-based narrative review of a century of Taraxacum officinale research (TOR), uncovering patterns, trends, themes, and advancements in the field to provide insights for future investigations. The study followed PRISMA guidelines and utilized the Scopus database with MeSH terms for bibliographic data retrieval. Scientometric mapping employed VOSviewer and R-package-based Bibliometrix, while extracted themes were reviewed narratively. A detailed analysis of TOR was achieved by including only original studies. Results: The findings include the extensive duration of TOR since 1908 and its significant growth, particularly in the last two decades. China emerges as the most productive country, but the United States leads in recognizable and collaborative TOR. The thematic map displays dynamic and diverse themes, with a rich knowledge structure revealed through the analysis of term co-occurrence. The year 2016 represents a turning point in the thematic map, marked by numerical growth and thematic bifurcation. The study extracted several main research topics within the field of TOR, including germination, antioxidant activity, bioherbicide, oxidative stress, Taraxacum kok-saghyz, and heavy metals. These topics represent key areas of investigation and provide insights into the diverse aspects of research surrounding T. officinale. Additionally, emerging topics in TOR encompass toxicity, metabolomics, dandelion extract, and diabetes mellitus. Conclusions: The study consolidated knowledge, highlighted research gaps, and provided directions for future investigations on TOR. [ABSTRACT FROM AUTHOR]

One of the main threats to freshwater resources is pollution from anthropogenic activities such as rapid urbanization and excessive agricultural nutrient runoff. Remote sensing technologies have been effectively used in monitoring and mapping rapid changes in the marine environment and assessing the overall health of freshwater ecosystems. The main goal of this study is to comparatively evaluate the performance of index-based and classification-based approaches in mapping dense floating algal blooms observed in Lake Burdur using Sentinel-2 imagery. For index-based mapping, algae-specific indices, namely the Floating Algae Index (FAI), Adjusted Floating Algae Index, Surface Algal Blooms Index (SABI), and Algal Blooms Detection Index (ABDI), were used. At the same time, pixel- and object-based Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Long Short-Term Memory Network (LSTM) were utilized for classification-based algal mapping. For this purpose, seven Sentinel-2 images, selected through time series analysis performed on the Google Earth Engine platform, were used as the primary dataset in the application. The results show that high-density floating algae formations can be detected over 99% by both indices and classification-based approaches, whereas pixel-based classification is more successful in mapping low-density algal blooms. When two-class thematic maps representing water and floating algae classes were considered, the maps produced by index-based FAI using an appropriate threshold value and the classification-based RF algorithm reached an overall accuracy of over 99%. The highest algae density in the lake was observed on July 13, 2021, and was determined to be effective in ~ 45 km2 of the lake's surface. [ABSTRACT FROM AUTHOR]

This article aimed at employing systematic analysis and bibliometric information to probe the emergence of the Future Time Perspective (FTP) study paradigm over the last fifty-five years. The scope and trajectory of the FTP field, common themes and future research lines across various clusters were mapped out to identify possible future research pathways that might significantly augment already knowledge and understanding established thus far. Authors have accomplished this by integrating bibliometric analysis with an extensive qualitative review of 648 articles published between 1956 and 2022. The content analysis and bibliometric analysis, aided by co-citation analysis, bibliographic coupling, and thematic and conceptual mapping, were taken to identify recent developments, potential prospects, impactful authors and prominent nations and organizations. While bibliometric analysis allowed us to map the evolving structure of the FTP literature, it also aided the content analysis of emerged clusters, enabling us to visualize literature changes over time, link knowledge to practice, and present future research prospects across the clusters. The five research clusters and future research viewpoints concerning each cluster emerged and was unearthed that, despite the multiplicity of studies, the FTP literature has evolved around some distinct themes with a fundamental set of authors hailing from the USA, Germany, Netherlands, China and Canada. The evidence indicates that FTP is a multifaceted construct emerging as a distinct and independent research discipline with many fruitful areas for further academic, social, industrial/organizational psychological, and behavioral inquiry. The authors are mindful that the current study demonstrates the overall progression and prominence of FTP literature by employing bibliometric and content analysis techniques. The outcomes of this study might be helpful for research scholars in persuading their research endeavors. [ABSTRACT FROM AUTHOR]

Domain-specific mesoscale landslide susceptibility mapping (LSM) and risk assessment was carried out along National Highway (NH44) of Jammu and Kashmir, Western Himalaya. The methodology proposed in this study broadly consist three stages including the (1) pre-field component for preliminary thematic map preparation, (2) field component for ground data collection and validation, and (3) post-field component for data updating, processing, and integration. High-resolution Earth Observation (EO) images (Cartosat-DEM-10 m, Cartosat-1 PAN image-2.5 m, Google Earth image-4 m) and other ancillary datasets (SoI topographic, and geological maps) supplemented with extensive field survey were used to generate main causative geo-factor maps for analysis. Slope facet used as a basic unit of mapping preliminarily classified the area into rocky (65.7%) and overburden covered (34.2%) slopes, respectively. An updated inventory of 117 landslide incidence zones comprising 50 debris slides, 34 rockfalls, 20 rock slides, 5 rock topples, 2 debris flows and 6 old slide zones was generated. Depending upon the type and nature of material involved in the slope failure, facets were further classified into debris slide domain, rock slide domain, cut-slope domain and no slide domain for detailed analysis and treatment. The geo-factor maps were weighted using knowledge driven ratings for each factor class as per domain-specific facet using Landslide Susceptibility Estimated Rating (LSER) scheme. The sum up of LSER values for individual causative factors calculated the Total Estimated Susceptibility Values (TESV) that classified the entire area into low, moderate and high susceptibility classes covering an area of 39.8%, 40.0% and 20.1%, respectively. The validation of LSM against high-resolution landslide inventory indicated a higher level of performance of the adopted methodology for the study area. About 80.0% and 10.4% of slope failure incidences coincided perfectly well with high and moderate susceptibility classes. Moreover, the human settlements, agriculture land, roads and bridges, stone crushers and other strategic civil structures (i.e., tunnels, electric line poles and towers, etc.) are the main elements at high risk in the area. [ABSTRACT FROM AUTHOR]

The challenge of urban growth and land use land cover (LULC) change is particularly critical in developing countries. The use of remote sensing and GIS has helped to generate LULC thematic maps, which have proven immensely valuable in resource and land-use management, facilitating sustainable development by balancing developmental interests and conservation measures. The research utilized socio-economic and spatial variables such as slope, elevation, distance from streams, distance from roads, distance from built-up areas, and distance from the center of town to determine their impact on the LULC of 2016 and 2019. The research integrates Artificial Neural Network with Cellular Automta to forecast and establish potential land use changes for the years 2025 and 2040. Comparison between the predicted and actual LULC maps of 2022 indicates high agreement with kappa hat of 0.77 and a percentage of correctness of 86.83%. The study indicates that the built-up area will increase by 8.37 km2 by 2040, resulting in a reduction of 7.08 km2 and 1.16 km2 in protected and agricultural areas, respectively. These findings will assist urban planners and lawmakers to adopt management and conservation strategies that balance urban expansion and conservation of natural resources leading to the sustainable development of the cities. [ABSTRACT FROM AUTHOR]

Mapping pressures to species is key to identify where biodiversity is at risk and providing relevant information to direct conservation actions. Decision-making to minimise pressures requires the determination of specific target actions at a high level of detail. However, the trade-off between cost and effort to generate this information often leads to the production of generalised pressure maps, named coarse maps, covering the most relevant pressures and their proxies. Here we aimed to disentangle whether the cost and effort of mapping fine pressures is worthwhile to inform decision making, by comparing how fine and coarse maps identify "where" and "how" management actions should be derived. Comparing the extend of both map types as well as its capacity to identify risk areas. We focused on three main pressures: agricultural intensification, human intensification, and land abandonment. The study was carried out in Catalonia for local decision-making, but the results can be applied in other EU regions or elsewhere, also for local decisions-making. We found that the Jaccard's similarity index between coarse and fine pressure maps was always below 0.3 indicating low overlap between fine and coarse maps. In particular, the coincidence between coarse and fine thematic maps within protected areas (PAs) was always below 50%. Both maps differed in the identification of risk areas inside three analysed PAs. Moreover, even when there was a total geographical overlap between coarse and fine maps, coarse maps lack information on which concrete pressure was actually present, making decision on actions needed difficult. Thus, we can conclude that fine maps can estimate more accurately both "where" and "how" to target concrete actions than coarser maps. Even in cases where the answer as to "where" to act is the same, fine maps provide more concrete information to provide guidance on "how" to act. Consequently, despite the high cost and effort involved in mapping pressures at a high level of detail, the final trade-off is positive. [ABSTRACT FROM AUTHOR]

Urbanization is a common issue worldwide that increases the demand for new urban services and requires land for a new settlement. This study focuses on improving the Analytical Hierarchy Process pairwise matrix using bivariate analysis to identify suitable zones for new urban areas in Latakia, Syria. MIF was used to rank the input thematic maps. Chi-square test and Cramer's V value were used to allocate decision values into the pairwise matrix instead of expert opinions. Weighted overlay analysis was applied to create the final urban suitability map, which was classified into five classes: unsuitable, low, moderate, high, and very high suitability areas with 0.23, 14.33, 57.75, 27.6, and 0.1% of total area, respectively. The primary outcome of this study is that bivariate analysis improved decision matrix reliability as the values were generated statistically without involvement from experts. The proposed method can be extended to include more parameters, different applications, and implementations. [ABSTRACT FROM AUTHOR]

Preemergence herbicides are traditionally applied uniformly throughout the area; however, weed control may vary due to spatial variability of the soil within the same area. Precision agriculture tools such as variable rate applications of herbicides improve weed control, making it necessary to know the physicochemical characteristics of the soil. The objective of this study was to map the spatial variability of sorption–desorption and agronomic efficiency of indaziflam and metribuzin for weed management in a field of 17.5 ha of Minas Gerais, Brazil. Fifty-five soil samples were collected (0–10 cm depth) and based on their physicochemical characteristics and the sorption and desorption coefficients for indaziflam and metribuzin, determined by a batch equilibrium method, thematic maps were generated for each variable in QGIS (Quantum Geographic Information System). In addition, the bioavailability concentration of each herbicide was determined, and its efficacy was evaluated in controlling Amaranthus hybridus and Eleusine indica in a representative soil sample. The sorption coefficient (Kd(s)) of indaziflam ranged from 6.9 to 40.5 L kg−1, the sorbed percentage (S%) from 61 to 86.6%, the desorbed percentage (D%) from 8.4 to 33.1%, and the total bioavailability (TB%) from 26 to 55.7%. The Kd(s) values of metribuzin ranged from 1.1 to 4.3 L kg−1, S% from 22.8 to 33.9%, D% from 17.2 to 22.0%, and TB% from 79.4 to 96.7%. Organic matter was highly correlated with the TB% of indaziflam (r = –0.8) and metribuzin (r = –0.7). Soil solution equilibrium concentration (Ce) of 1.9 g a.i. ha−1 of indaziflam controlled 80% of A. hybridus and E. indica. The Ce values of metribuzin were 55.2 and 111.2 g a.i. ha−1 to control 80% of A. hybridus and E. indica, respectively. Recommendations of varied doses provided reductions of 17.6% in the total application of indaziflam and 9.8% of metribuzin concerning the highest dose recommended in the field. The characterization of the soil physicochemical characteristics as well as the determination of the total bioavailability of indaziflam and metribuzin, by knowing the sorption–desorption coefficients, allowed for the recommendation of variable and precise doses of herbicides for the efficient management of A. hybridus and E. indica in preemergence, reducing potential negative environmental impacts. [ABSTRACT FROM AUTHOR]

Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands. [ABSTRACT FROM AUTHOR]

The concept and potential of Mobility as a Service (MaaS) has been the subject of significant debate in academia and industry for nearly a decade. There are several city-based Mobility as a Service (MaaS) pilots globally. There remains a significant lack of practitioner evidence of MaaS with the focus on city-based solutions rather than in rural and suburban areas. To that end, this paper asks four research questions to contribute to the gap in Rural MaaS (RMaaS) and Urban MaaS (UMaaS); firstly, is MaaS a mobility option for rural areas given the identified evidence in scientific literature? Secondly, how do practitioner experiences with MaaS (in all areas) differ considering factors like phraseology, geography, available modes, transportation, the origin and implementation stages? Thirdly, what practical learnings can be drawn from practitioners in the field? Fourthly, what is the future of MaaS for rural and urban areas. The research and findings are based upon grey literature and twenty semi-structured interviews with representatives from research or government organisations, public bodies, MaaS technology suppliers, transport operators and experts. Each participant discussed and contributed to the practicalities around real-world applications of MaaS in urban, regional, or rural areas. The analysis produced 2 applied tools which will be useful to practitioners interested in MaaS; a Thematic Map visualising the common matters emerging from the interviews revolving around 'People, Policy, Practice and Pilots (4Ps); a Practical Framework for Implementing MaaS tool, which can be used by any practitioner at any stage of a MaaS project. [ABSTRACT FROM AUTHOR]

Drought is a dangerous and expensive natural occurrence that slowly affects a country or region's ecology, economic, and social life. This paper aimed to delineate drought hazard zones in the Ba river basin, Vietnam, using the analytical hierarchy process (AHP) and geographical information system (GIS) technique. In this study, six thematic layers including rainfall, slope, land use, temperature, humidity, and drainage density were considered as prime criteria affecting drought occurrence. Weights were assigned to these six thematic maps depending on their significance. The acquired outcomes showed that the areas of the basin were facing various drought hazard levels including very low, low, moderate, high, and very high, each of which represents 1.36, 13.36, 39.2, 33.14, and 12.94% of the study area. The obtained findings were validated by comparing them to the results of the existing study and severe droughts that occurred in the past. The validation in this research confirmed the reliability and effectiveness of results achieved by AHP methods. The findings of the study contribute to enhancing drought preparation and resilience for communities at risk. [ABSTRACT FROM AUTHOR]

This paper aims at synthesizing the scientific research on coal fly ash and agriculture using bibliometric analysis. The research on fly ash and agriculture has grown at 6.7% annually during 1973–2022, where much attention has been received after 2007. The number of publications on coal fly ash and agriculture reached above 100 in the year 2010, which further increased to 299 by 2020. The research productivity has been assessed as the most influential countries, journals, and documents in terms of a number of publications and citations on fly ash and agriculture. India is the most productive country in terms of knowledge on coal fly ash and agriculture with 38% of the global publications, while Environmental Science and Pollution Research is the leading journal with 19 publications. The article on assessing the impact of fly ash incorporation in soil systems by Pandey and Singh (2010), having 349 citations with 26.85 citations per year is one of the leading publications globally. Further, science mapping has been conducted to comprehend the current research focus and discover the emerging themes for future research. The finding of the thematic map based on the level of development and importance indicate that FA can be effectively explored as soil-additive for improved physical, chemical and biological properties and enhanced plant nutrients. The findings provide several aspects of fly ash and suggest future research directions to study the potential of using coal fly ash in agriculture to gain an agronomic advantage. [ABSTRACT FROM AUTHOR]

Multiscale thematic maps of vegetation cover of the eastern Bolshezemelskaya tundra model area have been analyzed in this work. The primary mapping data has been obtained by processing satellite (Quickbird (Qb), Landsat TM5 (L5)) and aerial (DJI Phantom 2 (unmanned aerial vehicle (UAV)) images. Same imaging dates, survey conditions, and the spectral channel ranges of satellite radiometers have determined the identity of the vegetation cover characteristics on the satellite images. Homogeneous areas have been used for spectral signatures calculation of classes (Qb and L5 classifications) and have been obtained based on UAV imagery. A comparison of aerial and satellite images of the model area have showed that the bulk of the Qb image contained mixed pixels with a composition of the dominant class below 50%. Only 14.6% of the pixels had a share of the dominant class exceeding 80%. The majority (53.8%) of such homogeneous image elements included water surface classes (39.2%) and willow (24.6%). The number of homogeneous pixels of L5 (composition of more than 50% of the surface belongs to the same Qb class) did not exceed 14.1%. The spectral brightness coefficients for homogeneous pixels had high convergence between Qb and L5. Mixed pixels have been able to form spectral signatures with new values and sometimes with classes often missing inside. Overlapping the land cover and water surface class spectral features in mixed pixels formed spectra of eroded peatlands and bare soil. With reduction of resolution, an increase in the presence of an exposed peat class was noted (1.6- to 2.2-fold for transition UAV to Qb and 3.1- to 4.4-fold for Qb to L5, with the highest result being detected during UAV-L5 transition (6.9-fold)). Methods of spectral selection of etalon classes affected the convergence of classification results of spatially different images as well. A weak degree of conjunction was observed between UAV and Qb (30.3% (total) and 20.7% (κ)) and Qb and L5 classifications (44.5 and 30.3%, respectively). This index was negligible for UAV and L5 vegetation maps (28.5 and 15.5%). The main factors influencing the level of convergence and the ratio of class areas on different-scale images were the radiometric features of the class etalons and the spatial homogeneity of the mapped landscapes. [ABSTRACT FROM AUTHOR]

Currently, the development of modern cities creates the need for a balanced development of inner-city territorial spaces. The problem of unbalanced urban development in Ulaanbaatar is now particularly acute. There is a colossal intraurban differentiation of many factors, including the dynamics and location of the population, the degree of territory settlement, availability of infrastructure facilities, transport accessibility, etc. The authors present their study results, emphasizing the importance of spatial intradistrict analysis. First, the results serve as basic and primary indicators for the continuation of further scientific microdistrict research; second, they have a great practical orientation associated with the possibility of using them for making informed management decisions, in particular, for the prompt identification of priority problems, constraints and development reserves (including promising territories). In this work, various thematic maps have been created and areas have been identified by building types with a detailed analysis of spatial dynamics and population placement. A detailed analysis revealed the relationship between these factors. We have combined all the cartographic and statistical materials we have obtained into a single geoinformation system that allows us to conduct spatial data analysis and gain new knowledge at different levels. In this article, we tried to carry out zoning and identify some dependence of population dynamics from building types. Zoning is based on the study of spatial dynamics and population distribution and an analysis of the features and nature of the building. [ABSTRACT FROM AUTHOR]

Desertification assessment is vital to develop actions plans aimed to prevent desertification issues. Utilizing Geographic Information Systems (GIS) to manipulate and analyze data retrieved from various sources of data including satellite images and thematic maps, as well as the use of remote sensing through satellite images to retrieve environmental information on the earth's surface, are crucial tools to understand related environmental dangers, which is used to monitor desertification and investigate different desert conditions. In this study, different physical and environmental factors associated with land desertification including vegetation cover, water, drainage systems, geomorphology, and soil moisture, were extracted and evaluated using various remote sensing techniques. In addition, multi-temporal analysis of Landsat TM data is used in this study to examine the state of vegetation and growth of irrigated area between 1983 and 1997. A GIS tool is utilized to aggregate and analyze different factors including soil, land use, and climate. A decrease in vegetation cover was clearly observed based on these analysis results. A severe desertification of the natural vegetation cover is the primary cause of this predicament. Finally, many maps describing the actual situation of study area is obtained following the GIS layers examination, however, the most important maps are soil erosion, vegetation degradation, salinization and desertification. [ABSTRACT FROM AUTHOR]

This study employs Geographic Information Systems (GIS) tools and spatial data to evaluate water resource availability for livestock watering in Algeria's southwestern Wilaya of Naama. The research adopts a two-stage approach, starting with the creation of seven thematic maps encompassing livestock water needs, proximity to water sources, water quantities from boreholes, hillside reservoirs, wells, and springs, precipitation, and land use/land cover (LULC). Subsequently, an Analytic Hierarchy Process (AHP) is utilized to identify suitable areas within the Wilaya for livestock watering. Beyond its primary objective of establishing a benchmark for water resources to facilitate optimal and sustainable livestock management, this study also aims to assess suitable sites for livestock and provide a comprehensive evaluation of water resources for grazing. The findings reveal that the majority of the area is unsuitable for grazing due to limited water resources, with approximately 2.43% being "highly suitable" (S1), 13.42% "moderately suitable" (S2), and the remaining 84.15% categorized as "marginally suitable" (S3), "temporarily unsuitable" (N1), or "permanently unsuitable" (N2). These results underscore the significance of GIS and spatial analysis in natural resource management and emphasize the need for further research to refine the methodology. The data generated in this study will be invaluable to researchers and water stakeholders for informed decision-making in this sensitive zone. [ABSTRACT FROM AUTHOR]

Due to the correlation between water qualitative indices, their spatial variations are commonly estimated using semivariogram expressed methods, such as Kriging and cokriging. Some studies have tried applying multivariate statistics to identify the effect of various parameters on groundwater spatial variations; however, their estimations are eventually determined by Kriging family of methods. In this study, two multilevel Gaussian factor models (GF1 and GF2) are introduced to jointly model the multivariate data. Such an approach avoids the difficulties of maximum likelihood estimation, incorporating imperfect information to reach an effective decision. Thirty-five agricultural well samples were analyzed for EC and SAR, and other correlated variables over an area of about 1837 Km2 to prepare thematic maps of the groundwater quality classes, based on which administrative crops are suggested for the regional agriculture after selecting the best model for zoning groundwater quality. The GF2 model outperformed the ordinary Kriging in joint modelling of EC and Mg + Ca + Na. Moreover, the best fitting was obtained under Gaussian and Matern covariance functions. EC estimated values by Kriging and the multilevel Gaussian factor model were 2.18–5.17 ds/m and 2.53–4.54 ds/m, respectively. A notable resemblance was found between the spatial variation patterns obtained by the two methods in both EC and SAR variables. Despite relatively larger domains obtained from the Kriging model, such extreme values of EC and SAR covered small and insignificant zones of the study area. The areas estimated by the GF2 model and Kriging for the EC range 3–4.5 ds/m were relatively close (98.4% and 85.6% of the total area, respectively), while the values exceeding this range, covered very small, negligible fractions of total area (1.1% and 7.9%, respectively). Similar results were obtained for SAR estimates. The cultivable area signified by the two models were not significantly different, as shown by the allowable cultivation area maps generated. When GF2 model is applied, the whole study area is cultivable for all recommended crops in 90% and less yield potentials, while the limitations were insignificant, considering Kriging method. [ABSTRACT FROM AUTHOR]

The sustainability of groundwater aquifers requires evaluating several parameters, the most important of which are hydraulic parameters. Therefore, the essential aim of this research is to develop a management plan for the Moghra aquifer in order to prevent the expanding of water level decline and degradation of groundwater quality due to overexploitation and scarcity of recharge. To achieve this goal, all aquifer hydraulic parameters such as transmissivity, hydraulic conductivity, radius of interference, specific capacity, resulted drawdown, well loss, formation loss, well efficiency, and optimum safe yield had been measured for 40 groundwater wells drilled in the new reclaimed areas of Moghra Oasis. Based on geographic information system (GIS), hydrogeological cross sections and thematic maps for all parameters were created such as aquifer thickness, water table, groundwater flow direction, drawdown and groundwater salinity maps. The results revealed that clay and shale beds separated the three water-bearing formations of the Moghra aquifer. The aquifer-saturated thickness ranged from 30 and 102 m, and the groundwater level was below the mean sea level for all wells (ranges from − 72 to − 26.6 m). The calculated hydraulic parameters based on the analysis of long-duration pumping tests indicated that the studied aquifer has a wide variety of transmissivity (T) between 631 and 3768 m2/day, hydraulic conductivity (K) between 13.4 and 104.6 m/day, radius of influence from 126.3 to 581.3 m and specific capacity between 377.14 and 883.72 m2/day. On the other hand, the evaluation of existing drilled wells performance based on the results of step tests showed that well loss coefficient ranges between 0.0004749 and 0.0676 (h2/m5), formation loss coefficient varies from 3.34 × 10–8 to 4.80 × 10–6 (h/m2), well efficiency (γ) ranged from 50.53 to 98.08%, and optimum safe yield ranged from 40 to 98 (m3/h). Results of aquifer mapping and pumping tests can be more important for solving water scarcity issues, non-polluting water issues, health issues, and source of fresh water on the surface of the earth. The characterization of aquifer parameters in the study area, however, should be a significant component in the scientific planning and sustainability of groundwater. [ABSTRACT FROM AUTHOR]

Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor mapping is the distinction between acoustically similar substrates, such as mixed sediments from rhodoliths. Rhodolith beds are a biogenic substrate that provides important ecological services, and are typically classified as a single categorical substrate type—though nodules coverage may be spatially variable. Recently, multispectral acoustic backscatter has demonstrated great potential to improve thematic seafloor mapping compared to single-frequency systems. This work employs multispectral multibeam backscatter and underwater imagery to characterize and map rhodolith beds in the Costa das Algas Marine Protected Area (Brazil). A support vector machine classifier was used to classify multifrequency backscatter mosaics according to rhodolith classes identified from underwater imagery. Results suggest that multispectral backscatter is effective both in providing information for mapping different proportions of rhodolith coverage and in predicting the presence or absence of these nodules. The backscatter of the lowest frequency was the most useful for distinguishing variable proportions of rhodolith coverage, and the two higher frequencies were better predictors of presence and absence. [ABSTRACT FROM AUTHOR]

This study uses geospatial modeling and Multi-Criteria Decision Analysis (MCDA) to assess the Groundwater Potential Zones (GPZs) in Cachar District, India. Twelve influencing factors, namely Geomorphology, geology, soil type, Land Use Land Cover (LULC), rainfall, slope, drainage density, lineament density, elevation, aspect, Topographic Ruggedness Index (TRI), and Topographic Wetness Index (TWI), are considered, and thematic maps are prepared in Geographical Information System (GIS) platform. To measure the weightages of these factors, Analytical Hierarchical Process (AHP) and Best Worst Method (BWM) are the MCDA techniques used. The GPZs are generated using weights and reclassified into low, medium, and high zones. The major portion of the region is classified as the medium potential zone, with 64.25% and 63.96% of the total area using AHP and BWM, respectively. The validation with groundwater data for the two GPZ maps reveals that 10 out of 12 locations have been predicted accurately. BWM, with a lesser comparison matrix, performed as efficiently as AHP and has proven to be a better MCDA technique in spatial modeling GPZ for sustainable groundwater conservation. [ABSTRACT FROM AUTHOR]

Santa Maria dell'Isola is a rocky promontory surrounded by the Tyrrhenian Sea and located in Tropea municipality in Vibo Valentia Province (Calabria, southern Italy) (Fig. The preliminary results discussed herein suggest that the possible causes of the instability phenomena are imputable to the sandstone rocks' weak nature, the rock masses' high fracturing state, and the intense erosive processes by sea wave energy at the cliff foot. They show the topographic changes caused by rocks detached and the material accumulation at the foot of the cliff Conclusion Assessing the cause of the slope instability and focusing on site-specific geological characteristics are crucial steps before projecting suitable consolidation interventions. [Extracted from the article]

Objectives: Radiomics is the high-throughput extraction of mineable and—possibly—reproducible quantitative imaging features from medical imaging. The aim of this work is to perform an unbiased bibliometric analysis on Radiomics 10 years after the first work became available, to highlight its status, pitfalls, and growing interest. Methods: Scopus database was used to investigate all the available English manuscripts about Radiomics. R Bibliometrix package was used for data analysis: a cumulative analysis of document categories, authors affiliations, country scientific collaborations, institution collaboration networks, keyword analysis, comprehensive of co-occurrence network, thematic map analysis, and 2021 sub-analysis of trend topics was performed. Results: A total of 5623 articles and 16,833 authors from 908 different sources have been identified. The first available document was published in March 2012, while the most recent included was released on the 31st of December 2021. China and USA were the most productive countries. Co-occurrence network analysis identified five words clusters based on top 50 authors' keywords: Radiomics, computed tomography, radiogenomics, deep learning, tomography. Trend topics analysis for 2021 showed an increased interest in artificial intelligence (n = 286), nomogram (n = 166), hepatocellular carcinoma (n = 125), COVID-19 (n = 63), and X-ray computed (n = 60). Conclusions: Our work demonstrates the importance of bibliometrics in aggregating information that otherwise would not be available in a granular analysis, detecting unknown patterns in Radiomics publications, while highlighting potential developments to ensure knowledge dissemination in the field and its future real-life applications in the clinical practice. Clinical relevance statement: This work aims to shed light on the state of the art in radiomics, which offers numerous tangible and intangible benefits, and to encourage its integration in the contemporary clinical practice for more precise imaging analysis. Key Points: • ML-based bibliometric analysis is fundamental to detect unknown pattern of data in Radiomics publications. • A raising interest in the field, the most relevant collaborations, keywords co-occurrence network, and trending topics have been investigated. • Some pitfalls still exist, including the scarce standardization and the relative lack of homogeneity across studies. [ABSTRACT FROM AUTHOR]

The current study used vertical electrical sounding (VES), borehole (BH) data, Remote Sensing (RS), and Geographic Information System (GIS) techniques to identify groundwater potential zones in the coastal area of Akwa Ibom state, Nigeria, for the first time. This research aimed at producing groundwater potential zone map that can divide the study region into separate zones based on their groundwater potential ranking. The deployed method integrated VES procedure utilizing the Schlumberger electrode configuration some core samples for estimation of porosity, Satellite Shuttle Radar Topography Mission (SRTM), Digital Elevation Model (DEM), which served as input data for RS and GIS. Thematic maps of lineament density, lithology, land use and land cover, drainage density, and slope were created as GIS layers in a geo-database. Weightages were assigned based on a pair-wise assessment of the components that appear to be essential in retaining, storing, and transporting groundwater. The Analytical Hierarchy Process (AHP) was used in a GIS setting to merge five thematic maps of elements controlling groundwater occurrence and movement using weighted overlay. Results show that aquifers with high thickness and depths are clustering around VES 9, VES 14, and VES 15 that have the highest aquifer thickness in the range of 219–262 m and the highest aquifer depth in the range of 222.09–264.74 m. The highest aquifer resistivity in this area ranges from 2963 to 3683 Ωm. The hydraulic conductivity of the area is highest around the south-eastern part of the study area, with maximum value of 3.43 m/day. The transmissivity increases in the northern part of the study area, while the eastern parts showed the lowest values. The highest aquifer resistivity in this area ranged from 2963 to 3683 Ωm. Inference from analysis indicated that the most important element was soil type (43%), followed by lineament density (33%) and slope (13%). Land use/land cover was discovered as a marginal contributor to groundwater in the research region, accounting for about 4% of the total contributors. The study CR determined to be 0.043884, is much lower than the 0.10 consistency threshold and hence the justification of the results. The result of the overlay of the geophysical survey on the groundwater potential zones obtained from the RS, GIS, and VES techniques done in the first time in the study area has shown seamlessly that the study area has high groundwater prospectivity for subsistent and commercial extractions. [ABSTRACT FROM AUTHOR]

Understanding natural phenomena with the help of modern scientific approaches helps to reach sustainable solutions for current and future water-related problems. In this context, present study aims to assess relative influencing level of physical factors in controlling groundwater level, using a novel grid-based delineation technique, in Lower Palar River Basin, in Kanchipuram and Chengalpattu districts of South India. The influencing factors viz-a-viz: rainfall, soil texture, land use/land cover, terrain slope, geomorphology, lithology, and drainage characteristics were considered for the study. Archived data (2011 to 2020) of monthly rainfall at four rain gauge stations and monthly groundwater level of 22 locations, soil texture, lithology, and geomorphology data were considered for the study. SRTM digital elevation model with 30-m resolution was used for analyzing drainage characteristics and terrain slope. Thematic maps for considered factors were prepared, using common grid delineation method in GIS platform that divided study area into 52 grids, to inter-relate the discrete and continuous parameters with groundwater level. Results indicate that level of influence increases in the order of precipitation followed by lithology, land use/land cover, terrain slope, geomorphology, infiltration number, and soil texture. The study shows groundwater resilience is highly influenced by soil texture and infiltration number compared to other factors considered. It can be concluded that grid-based delineation successfully identifies grids with significant influence of individual factors by comparing with groundwater resilience. Common grid-based delineation method proves to be more effective in assessing groundwater resilience and can be used more efficiently in groundwater studies. [ABSTRACT FROM AUTHOR]

The present study aims to examine the spatio-temporal and seasonal fluctuation of groundwater levels in an eastern Indian semi-arid region. Also, it attempted to investigate the involvement of different significant groundwater usage factors in causing such variations and trends. Furthermore, by evaluating temporal patterns and the influence of the crucial drivers, generate meaningful predictions for raising community awareness about the future. A combination of statistical, spatial analysis, and machine learning techniques were used to fulfill the objectives. Overall, the findings revealed that the south-eastern corner (consisting of Bundwan and Barabazar Blocks), the far western region (especially Jhalda I and II Blocks), and some of the eastern Blocks are most vulnerable to groundwater scarcity. The monitoring stations in this region are typically suffering a significant declining trend in groundwater level, with a substantial amount of Sen's Slope. In contrast, the centrally positioned Blocks have lesser susceptibility. The MLR analysis and spatial thematic maps demonstrate a strong association between this spatial pattern of declining groundwater table and the groundwater drivers in consideration. Thus, it is acceptable to suggest that drivers from the human world must be included in the groundwater management planning of the Purulia district. Finally, the predictions from the time series confirm that if no interventions are implemented, the average groundwater level will decline by 2.5 m by 2030. Therefore, Purulia urgently requires a realistic plan to prevent future generations from becoming refugees in their own land. [ABSTRACT FROM AUTHOR]

Flooding is one of the most catastrophic natural disasters in terms of provoking socio-economic losses. The current study is to foster a flood susceptibility map of Krishna District in Andhra Pradesh (AP) through integrating remote sensing data, geographical information system (GIS), and the analytical hierarchy process (AHP). Eleven factors, including elevation, slope, aspect, land use/land cover (LULC), drainage density, topographic wetness index, stream power index, lithology, soil, precipitation, and distance from the streams, are considered for identifying and evaluating the spatial distribution of critical flood-susceptible regions. Thematic maps of different factors were derived in GIS using remote sensing data obtained from Sentinel-2A (satellite sensor), shuttle radar topography mission digital elevation model (SRTM DEM v3), and other scientific data products. An analytical hierarchy process is a mathematical approach for decision support, primarily based on the weight and rank of different causative factors. AHP technique is implemented for flood hazard modeling and ascertaining the Flood Hazard Index (FHI) to produce a flood susceptibility map. Different thematic maps weighed with the AHP framework are combined using overlay analysis to produce the flood susceptibility map of the study region. The outcomes of the study demonstrate the potential of GIS and AHP in providing a premise to recognize the vulnerable areas that are susceptible to flood. According to the findings, the Flood Hazard Index is 42% and the study region is classified into very high, high, moderate, low, and very low susceptible, respectively. Following that, historical flood data was used to validate the accuracy of the generated flood susceptibility map. This shows that a maximum of 90% of the data points are within floodplain. [ABSTRACT FROM AUTHOR]

This paper aims at analyzing the research productivity and scientific knowledge discovery of the COVID-19 pandemic in agriculture using a bibliometric analysis approach. A total of 1514 research papers indexed in the Scopus database, covering a period of 2020 to 2022, are processed using VOSviewer and R-Studio software. The analysis of research productivity indicates that the number of research publications on COVID-19 and agriculture has exponentially increased globally, and about 80% of the research papers have been published in the top 10 countries led by the USA, India, and China. The countries are increasingly collaborating in undertaking research on COVID-19 and agriculture. Furthermore, major journals and articles with citations have been extracted to analyze the leading publication avenues and focused areas of research. The science mapping is done using co-occurrence and thematic map. With the help of co-occurrence analysis, six clusters are identified depicting major research themes, i.e., COVID-19 and agricultural supply chain disruption, COVID-19 and human health issues and coping strategies, COVID-19 and non-human and animal health, COVID-19 pandemic and environment and pollution, COVID-19 and healthcare and treatment, and COVID-19 and food nutrition from dairy and meat products. The thematic map analysis identifies potential research areas such as mental health, anxiety, and depression in the agricultural system, which may help in setting future research agenda and help devising policy supports for managing the agriculture sector better during crisis. The paper also highlights the theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Present study deals with the application of statistical and geostatistical modelling to analyse spatio-temporal variation in water quality of selected 466 km in the lower stretch of river Ganga (545 km). Six important physicochemical parameters, e.g. water temperature, transparency, pH, dissolved oxygen, alkalinity and specific conductivity, each of thirteen selected sites of monsoon and pre-monsoon seasons are observed for the year 2014. Statistical modelling such as factor analysis is used to identify significant variables for variation in water parameters, whereas geostatistical modelling, e.g. ordinary kriging (OK) is used for spatial distributions of the water parameters in the river. Result showed alkalinity and specific conductivity during monsoon season, while transparency, pH, dissolved oxygen and specific conductivity in pre-monsoon season correlated to maximum variation in water quality. Geostatistical modelling, ordinary kriging (OK)-based interpolation model for water parameters showed more than 85% correlation at validation sites. The generated thematic map of spatial distribution for alkalinity during monsoon season and specific conductivity in both pre-monsoon and monsoon season showed an increasing trend from northern part (upward stream) to southern part (downward stream) of the river stretch. Whereas, in case of transparency, pH and dissolved oxygen, a reverse trend was observed as they increased from southern part (downward stream) to northern part (upward stream) of the river in pre-monsoon season. This combined approach for spatio-temporal water quality assessment in River Ganga can provide useful information for researchers and policy-makers for sustainable management of lower stretch of the River Ganga. [ABSTRACT FROM AUTHOR]

Thematic maps are essential tools in precision agriculture to demonstrate the information of spatially distributed phenomena. A thematic map can be created from sampling data, a standard procedure for soil attributes. Interpolation methods are used to estimate data in unknown locations, such as inverse distance weighting (IDW) and ordinary Kriging (OK). For both interpolators, it is essential to use the appropriate parameters to estimate values in non-sampled locations, either the exponent value and the number of neighbors for IDW, or the theoretical model adjusted to the experimental semivariogram for OK. Thus, this trial aims at adopting additional criteria in selecting interpolators and evaluating their performance. AgDataBox platform's data interpolation module was improved, where the process of selecting the interpolator and determining its parameters considers the criteria (i) effective spatial dependence index, (ii) the first semivariance significance index, and (iii) slope of the model ends index. The experimental data come from an experiment in two agricultural areas in Brazil, using grids with good sampling density (2.7, 2.6, and 3.5 points per ha). It was observed that, usually, the application method of the three new criteria selected different models for a dataset and this must be considered in the interpolator selection process. Thematic maps varied from 0.1 to 64%, according to the coefficient of relative deviation, when comparing the three methods of applying the selection criteria. [ABSTRACT FROM AUTHOR]

With the massive progress in science and technology, increasing populations, and urbanization demands, the need for newly developed urban areas raising. According to primary criteria, site suitability analysis provides a good way to identify and suggest the best and most appropriate sites. Multicriteria decision analysis (MCDA) is one of these techniques. This study applied a geospatial decision support system with a combination of MCDA and bivariate analysis to find the suitability map for urban development. The Multi-Influence Factor (MIF) is used to rank the input thematic maps according to their interaction, while the chi-square and Cramer's V-value (bivariate analysis) are used to determine pairwise comparisons in the Best Worst method (BWM). BWM is used to compute the weight of each thematic map. Fuzzy logic was used to renovate the classified layer values ​​into fuzzy values, after which the final site suitability map was derived using the fuzzy overlay. The study provides insights into optimizing the reliability and consistency of pairwise comparisons in BWM using bivariate analysis. [ABSTRACT FROM AUTHOR]

Groundwater is a crucial natural resource for providing reliable and long-lasting water supplies across the globe. The integrated approach used in the current study involved the use of multiple techniques to assess groundwater potential zones (GWPZs) and identify suitable areas for artificial recharge sites. The methods used in the study were a combination of geographic information system (GIS), analytic hierarchy process (AHP), and fuzzy analytic hierarchy process (Fuzzy-AHP) to accomplish this goal. The study considered multiple thematic maps, such as drainage density, elevation, geomorphology, slope, curvature, topographic wetness index (TWI), geology, distance from the river, land use and land cover (LULC), and rainfall, to determine the GWPZs. AHP and Fuzzy-AHP were used to weight thematic maps based on their relative importance in controlling groundwater availability and recharge, and then a weighted overly analysis in a GIS environment was utilized to derive the final GWPZs map. After completing the weighting of thematic maps, both AHP and Fuzzy-AHP models categorized GWPZs into low, moderate, and high categories in the study area. In this study area, GWPZs were classified as poor, moderate, and high using both the AHP and Fuzzy-AHP models. According to the AHP model, 5.41% of the area's GWPZs were categorized as poor, 70.68% as moderate, and 23.91% as high. The Fuzzy-AHP model, on the other hand, categorized 4.92% as poor, 69.75% as moderate, and 25.33% as high. To validate these results, the receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to explore the prediction accuracy, resulting in an accuracy rate of 70.1% for AHP and 71% for Fuzzy-AHP. These findings suggest that the Fuzzy-AHP model is effective in accurately identifying GWPZs in this area. Additionally, using remote sensing (RS) and GIS, the current study created a map by overlaying the lineament and drainage maps to determine suitable locations for artificial recharge. One-hundred-forty suitable locations for artificial recharge sites were identified based on Fuzzy-AHP. The study's reliable findings assist decision-makers and water users in the research area to use groundwater resources sustainably. This information aids in sustainable planning and management of groundwater resources, ensuring their availability and sustainability for future generations. [ABSTRACT FROM AUTHOR]

The largest reservoir of drinkable water on Earth is surface water. It is crucial for maintaining ecosystems and enabling people to adapt to diverse climate changes. Despite surface freshwater is essential for life, the current research shows a striking lack of understanding in its spatial and temporal dynamics of variations in outflow and storage across a sizable country: India. Numerous restrictions apply to current research, including the use of insufficient machine learning techniques and limited data series. This work uses cutting-edge and SOTA-method to use the available data and machine learning to accurately understand spatial and temporal dynamics of variations in surface freshwater outflow and storage using extended data series. The authors did the examination of thematic maps produced using ArcMap 10.8 from June'2005 to June'2020 using JRC dataset to track changes in the intensity of surface water. Google Earth Engine in Python API has been devised to detect changes in surface water levels and quantifying shifting map trends. Raster image viewing, editing, and calculation are done with ArcMap. For determining the relationship between declines in Surface water levels, changes in rainfall intensity and land surface temperature, variables were averaged over 13 rivers for 15 years. The change in surface water is reliant on independent variables of change in land surface temperature and rainfall intensity. The authors use the correlation between these parameters to achieve an average R-squared adjusted value of 0.402. The study's findings contribute to a better understanding of the matter and can be used across the world. [ABSTRACT FROM AUTHOR]

This study utilizes bibliometric analyses to map and visualize the development, conceptual structure, and thematic evolution of the Islamic Banking and Finance (IB&F) scholarly research. It analyses 464 WoS IB&F research publications of 921 authors comprising 58 countries published over three decades from 1990 to 2019. The results reveal that (i) collaboration among countries is limited and institutional collaboration can be described as a "locally concentrated and globally isolated," (ii) the IB&F research is a type of "small-world-network" where few authors and journals dominate the networks and play a central role in the diffusion of knowledge and the "homophily impact" is present among the leading authors of the IB&F research, (iii) the networks in IB&F research reflects the "Matthew Effect," implying that few authors have a more significant number of networks compared to the rest of authors. The study has also identified the conceptual structure and thematic trends in the IB&F research and provides avenues for future research. [ABSTRACT FROM AUTHOR]

The inadequate public water supply in Osogbo metropolis, Southwest Nigeria, necessitates the extraction of groundwater from shallow aquifers via hand dug wells and boreholes as an alternative source of potable water. However, crystalline rock aquifers are localized and discontinuous with limited vertical and lateral extent. This therefore informed the use of electrical resistivity attributes to appraise the groundwater prospect of the area. One hundred and nine (109) depth sounding data were acquired and quantitatively interpreted to generate the subsurface geo-electric layer parameters (resistivities and thicknesses). Weathered basement aquifer resistivity and thickness, bedrock relief, and resistivity anisotropy coefficient thematic maps were created using the Krigging interpolation technique. The thematic maps were integrated to evolve the composite groundwater prospect map of the area using the weighted linear combination overlay technique. Borehole yield data were used to validate the map. Three (3) to six (6) layers were delineated. These included the topsoil (13–4697 Ωm; 0.2–6.5 m), laterite (500–4727 Ωm; 0.3–7.5 m), weathered basement (7.0–641 Ωm; 0.8–57.6 m) (main aquifer), partly weathered/fractured basement aquifer (18–826 Ωm; 1.8–27.9 m), and fresh basement (485–20,728 Ωm). Weathered basement resistivity, weathered basement thickness, bedrock relief, and resistivity anisotropy coefficient thematic maps showed range < 100–641 Ωm; < 10-> 40 m; > 340 m (ridge), 320–340 m (pediment), < 320 m (basement depression), and 1.00–3.80 unit respectively. The composite groundwater prospect map revealed very low, low, moderate, high and very high groundwater prospect zones. The study concluded that the groundwater prospect of Osogbo metropolis was generally very low to moderate. [ABSTRACT FROM AUTHOR]

Groundwater is an essential reservoir of freshwater. It is becoming more critical for arid and semi-arid regions due to climate changes and long drought periods. The proposed work aims at providing a solution for data scarcity regions in addition to the improvement of the reliability of machine learning methods for groundwater mapping due to low samples. We propose the use of neighboring data by defining an extended study area that includes the study area where extra boreholes are known. In addition, we propose the use of piezometric contours to augment the size of the dataset using artificial boreholes. Seven thematic maps are prepared to characterize the study area and the extended area: digital elevation, slope, drainage, lithology, lineaments, rainfall, and land use. On the other hand, random forest, SVM, and neural networks are used to learn an appropriate model on the augmented dataset. To validate the work, 233 boreholes are classified based on their groundwater static level. In addition, several metrics are used to validate the performance such as ROC-AUC, accuracy, and κ score. The Random forest shows the best performance in terms of all measures: AUC = 0.95, accuracy = 79.82%, and κ = 0.73. The obtained maps show that 7% of the study area can have very high potential which can be used for resource management. [ABSTRACT FROM AUTHOR]

This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that net recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98% of the study area falls into a very high vulnerability class, 31.90% falls into a high vulnerability, 23.52% falls into the average vulnerability, 21.75% falls into a low vulnerability, and 9.85% falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution. [ABSTRACT FROM AUTHOR]