Subjects -> ENVIRONMENTAL STUDIES (Total: 992 journals)
    - ENVIRONMENTAL STUDIES (885 journals)
    - POLLUTION (31 journals)
    - TOXICOLOGY AND ENVIRONMENTAL SAFETY (58 journals)
    - WASTE MANAGEMENT (18 journals)

ENVIRONMENTAL STUDIES (885 journals)                  1 2 3 4 5 | Last

Showing 1 - 200 of 378 Journals sorted alphabetically
ACS Chemical Health & Safety     Hybrid Journal   (Followers: 5)
ACS ES&T Engineering     Hybrid Journal   (Followers: 10)
Acta Brasiliensis     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 11)
Acta Environmentalica Universitatis Comenianae     Open Access   (Followers: 1)
Acta Limnologica Brasiliensia     Open Access   (Followers: 4)
Acta Oecologica     Hybrid Journal   (Followers: 12)
Acta Regionalia et Environmentalica     Open Access   (Followers: 1)
Advanced Electronic Materials     Hybrid Journal   (Followers: 7)
Advanced Energy and Sustainability Research     Open Access   (Followers: 7)
Advanced Sustainable Systems     Hybrid Journal   (Followers: 7)
Advances in Ecological Research     Full-text available via subscription   (Followers: 45)
Advances in Environmental Chemistry     Open Access   (Followers: 11)
Advances in Environmental Sciences - International Journal of the Bioflux Society     Open Access   (Followers: 21)
Advances in Environmental Technology     Open Access   (Followers: 1)
Advances in Life Science and Technology     Open Access   (Followers: 23)
Advances in Tropical Biodiversity and Environmental Sciences     Open Access   (Followers: 5)
Aeolian Research     Hybrid Journal   (Followers: 6)
African Journal of Environmental Science and Technology     Open Access   (Followers: 5)
Agricultura Tecnica     Open Access   (Followers: 5)
Agricultural & Environmental Letters     Open Access   (Followers: 3)
Agro-Science     Full-text available via subscription   (Followers: 3)
Agroecological journal     Open Access  
Agronomy for Sustainable Development     Open Access   (Followers: 22)
Agrosystems, Geosciences & Environment     Open Access   (Followers: 7)
Amazon's Research and Environmental Law     Open Access   (Followers: 5)
Ambiência     Open Access  
Ambiens. Revista Iberoamericana Universitaria en Ambiente, Sociedad y Sustentabilidad     Open Access   (Followers: 1)
Ambiente & sociedade     Open Access   (Followers: 3)
Ambiente & Agua : An Interdisciplinary Journal of Applied Science     Open Access   (Followers: 1)
American Journal of Energy and Environment     Open Access   (Followers: 5)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Environmental Protection     Open Access   (Followers: 9)
American Journal of Environmental Sciences     Open Access   (Followers: 11)
American Naturalist     Full-text available via subscription   (Followers: 85)
Annals of Civil and Environmental Engineering     Open Access   (Followers: 3)
Annals of Environmental Science and Toxicology     Open Access   (Followers: 3)
Annals of GIS     Hybrid Journal   (Followers: 29)
Annals of Warsaw University of Life Sciences ? SGGW. Land Reclamation     Open Access  
Annual Review of Ecology, Evolution, and Systematics     Full-text available via subscription   (Followers: 89)
Annual Review of Environment and Resources     Full-text available via subscription   (Followers: 16)
Annual Review of Pharmacology and Toxicology     Full-text available via subscription   (Followers: 35)
Annual Review of Resource Economics     Full-text available via subscription   (Followers: 10)
Applied and Environmental Soil Science     Open Access   (Followers: 20)
Applied Ecology and Environmental Sciences     Open Access   (Followers: 30)
Applied Environmental Education & Communication     Hybrid Journal   (Followers: 19)
Applied Journal of Environmental Engineering Science     Open Access   (Followers: 2)
Aquatic Ecology     Hybrid Journal   (Followers: 39)
Aquatic Toxicology     Hybrid Journal   (Followers: 25)
Arcada : Revista de conservación del patrimonio cultural     Open Access   (Followers: 2)
Architecture, Civil Engineering, Environment     Open Access   (Followers: 4)
Archives des Maladies Professionnelles et de l'Environnement     Full-text available via subscription  
Archives of Environmental and Occupational Health     Hybrid Journal   (Followers: 12)
Archives of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 14)
Archives of Toxicology     Hybrid Journal   (Followers: 20)
Arctic Environmental Research     Open Access   (Followers: 1)
Asian Journal of Environment & Ecology     Open Access   (Followers: 1)
Asian Journal of Rural Development     Open Access   (Followers: 9)
Asian Review of Environmental and Earth Sciences     Open Access   (Followers: 3)
ATBU Journal of Environmental Technology     Open Access   (Followers: 5)
Atmospheric and Climate Sciences     Open Access   (Followers: 35)
Atmospheric Environment     Hybrid Journal   (Followers: 75)
Atmospheric Environment : X     Open Access   (Followers: 3)
Augm Domus : Revista electrónica del Comité de Medio Ambiente de AUGM     Open Access  
Austral Ecology     Hybrid Journal   (Followers: 18)
Australasian Journal of Environmental Management     Hybrid Journal   (Followers: 13)
Australasian Journal of Human Security     Full-text available via subscription   (Followers: 1)
Australian Journal of Environmental Education     Full-text available via subscription   (Followers: 11)
Basic & Clinical Pharmacology & Toxicology     Hybrid Journal   (Followers: 13)
Basic and Applied Ecology     Hybrid Journal   (Followers: 25)
Behavioral Ecology     Hybrid Journal   (Followers: 60)
Behavioral Ecology and Sociobiology     Hybrid Journal   (Followers: 38)
Biocenosis     Open Access  
Biochar     Hybrid Journal   (Followers: 3)
Biodegradation     Hybrid Journal   (Followers: 2)
Biodiversity     Hybrid Journal   (Followers: 30)
Biofouling: The Journal of Bioadhesion and Biofilm Research     Hybrid Journal   (Followers: 7)
Bioremediation Journal     Hybrid Journal   (Followers: 5)
BioRisk     Open Access   (Followers: 3)
BMC Ecology     Open Access   (Followers: 24)
Boletín Instituto de Derecho Ambiental y de los Recursos Naturales     Open Access  
Boletín Semillas Ambientales     Open Access  
Boston College Environmental Affairs Law Review     Open Access   (Followers: 7)
Bothalia : African Biodiversity & Conservation     Open Access   (Followers: 1)
Built Environment     Full-text available via subscription   (Followers: 5)
Bulletin of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 15)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Bumi Lestari Journal of Environment     Open Access  
Canadian Journal of Earth Sciences     Hybrid Journal   (Followers: 23)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 50)
Canadian Journal of Soil Science     Full-text available via subscription   (Followers: 14)
Canadian Water Resources Journal     Hybrid Journal   (Followers: 20)
Capitalism Nature Socialism     Hybrid Journal   (Followers: 27)
Carbon Resources Conversion     Open Access   (Followers: 3)
Case Studies in Chemical and Environmental Engineering     Open Access   (Followers: 1)
Casopis Slezskeho Zemskeho Muzea - serie A - vedy prirodni     Open Access  
Cell Biology and Toxicology     Hybrid Journal   (Followers: 12)
Chain Reaction     Full-text available via subscription  
Challenges in Sustainability     Open Access   (Followers: 12)
Chemical Research in Toxicology     Hybrid Journal   (Followers: 25)
Chemico-Biological Interactions     Hybrid Journal   (Followers: 3)
Chemosphere     Hybrid Journal   (Followers: 17)
Child and Adolescent Mental Health     Hybrid Journal   (Followers: 72)
China Population, Resources and Environment     Full-text available via subscription   (Followers: 4)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
City and Environment Interactions     Open Access   (Followers: 4)
Civil and Environmental Engineering     Open Access   (Followers: 8)
Civil and Environmental Engineering Reports     Open Access   (Followers: 9)
Civil and Environmental Research     Open Access   (Followers: 22)
CLEAN - Soil, Air, Water     Hybrid Journal   (Followers: 21)
Clean Technologies     Open Access   (Followers: 1)
Clean Technologies and Environmental Policy     Hybrid Journal   (Followers: 5)
Cleanroom Technology     Full-text available via subscription   (Followers: 1)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Climate Change Ecology     Open Access  
Climate Change Economics     Hybrid Journal   (Followers: 33)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Coastal Engineering Journal     Hybrid Journal   (Followers: 9)
Cogent Environmental Science     Open Access  
Columbia Journal of Environmental Law     Open Access   (Followers: 15)
Computational Ecology and Software     Open Access   (Followers: 11)
Computational Water, Energy, and Environmental Engineering     Open Access   (Followers: 5)
Conservation and Society     Open Access   (Followers: 14)
Conservation Letters     Open Access   (Followers: 51)
Conservation Science     Open Access   (Followers: 29)
Consilience : The Journal of Sustainable Development     Open Access   (Followers: 3)
Contemporary Problems of Ecology     Hybrid Journal   (Followers: 4)
Critical Reviews in Environmental Science and Technology     Hybrid Journal   (Followers: 15)
Critical Reviews in Toxicology     Hybrid Journal   (Followers: 26)
Cuadernos de Investigación Geográfica / Geographical Research Letters     Open Access  
Culture, Agriculture, Food and Environment     Hybrid Journal   (Followers: 25)
Culture, Agriculture, Food and Environment     Hybrid Journal   (Followers: 11)
Current Environmental Engineering     Hybrid Journal  
Current Environmental Health Reports     Hybrid Journal   (Followers: 2)
Current Forestry Reports     Hybrid Journal   (Followers: 1)
Current Landscape Ecology Reports     Hybrid Journal   (Followers: 2)
Current Opinion in Environmental Science & Health     Hybrid Journal   (Followers: 1)
Current Opinion in Environmental Sustainability     Hybrid Journal   (Followers: 17)
Current Research in Ecological and Social Psychology     Open Access  
Current Research in Environmental Sustainability     Open Access   (Followers: 2)
Current Research in Green and Sustainable Chemistry     Open Access   (Followers: 1)
Current Research in Microbiology     Open Access   (Followers: 27)
Current Sustainable/Renewable Energy Reports     Hybrid Journal   (Followers: 9)
Current World Environment     Open Access   (Followers: 7)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 31)
Developments in Earth and Environmental Sciences     Full-text available via subscription   (Followers: 3)
Developments in Earth Surface Processes     Full-text available via subscription   (Followers: 1)
Developments in Environmental Modelling     Full-text available via subscription   (Followers: 8)
Developments in Environmental Science     Full-text available via subscription   (Followers: 4)
Developments in Integrated Environmental Assessment     Full-text available via subscription   (Followers: 5)
Die Bodenkultur : Journal of Land Management, Food and Environment     Open Access   (Followers: 2)
Disaster Prevention and Management     Hybrid Journal   (Followers: 32)
Discover Sustainability     Open Access   (Followers: 3)
disP - The Planning Review     Hybrid Journal   (Followers: 1)
Divulgación Científica     Open Access   (Followers: 1)
Drug and Chemical Toxicology     Hybrid Journal   (Followers: 16)
Duke Environmental Law & Policy Forum     Open Access   (Followers: 7)
Dynamiques Environnementales     Open Access   (Followers: 1)
E3S Web of Conferences     Open Access   (Followers: 2)
Earth and Environmental Science Transactions of the Royal Society of Edinburgh     Hybrid Journal   (Followers: 6)
Earth Interactions     Open Access   (Followers: 13)
Earth Science Informatics     Hybrid Journal   (Followers: 5)
Earth System Governance     Open Access  
Earth System Science Data (ESSD)     Open Access   (Followers: 8)
Earth Systems and Environment     Hybrid Journal   (Followers: 3)
Earthquake Science     Hybrid Journal   (Followers: 14)
EchoGéo     Open Access  
Eco-Thinking     Open Access   (Followers: 5)
Ecocycles     Open Access   (Followers: 6)
Ecohydrology     Hybrid Journal   (Followers: 11)
Ecohydrology & Hydrobiology     Full-text available via subscription   (Followers: 4)
Ecologia Aplicada     Open Access  
Ecología en Bolivia     Open Access  
Ecological Applications     Full-text available via subscription   (Followers: 212)
Ecological Chemistry and Engineering S     Open Access   (Followers: 4)
Ecological Complexity     Hybrid Journal   (Followers: 7)
Ecological Engineering     Hybrid Journal   (Followers: 4)
Ecological Engineering : X     Open Access  
Ecological Indicators     Hybrid Journal   (Followers: 23)
Ecological Informatics     Hybrid Journal   (Followers: 4)
Ecological Management & Restoration     Hybrid Journal   (Followers: 15)
Ecological Modelling     Hybrid Journal   (Followers: 96)
Ecological Monographs     Full-text available via subscription   (Followers: 39)
Ecological Processes     Open Access   (Followers: 2)
Ecological Questions     Open Access   (Followers: 4)
Ecological Research     Hybrid Journal   (Followers: 12)
Ecological Restoration     Full-text available via subscription   (Followers: 23)
Ecologist, The     Full-text available via subscription   (Followers: 23)
Ecology     Full-text available via subscription   (Followers: 480)
Ecology and Evolution     Open Access   (Followers: 104)
Ecology Letters     Hybrid Journal   (Followers: 339)
EcoMat : Functional Materials for Green Energy and Environment     Open Access   (Followers: 3)
Economics and Policy of Energy and the Environment     Full-text available via subscription   (Followers: 14)
Économie rurale     Open Access   (Followers: 3)
Ecoprint : An International Journal of Ecology     Open Access   (Followers: 6)
Ecopsychology     Hybrid Journal   (Followers: 8)
Ecosphere     Open Access   (Followers: 9)
Ecosystem Services     Hybrid Journal   (Followers: 10)
Ecosystems     Hybrid Journal   (Followers: 33)

        1 2 3 4 5 | Last

Similar Journals
Journal Cover
Earth Science Informatics
Journal Prestige (SJR): 0.503
Citation Impact (citeScore): 2
Number of Followers: 5  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1865-0481 - ISSN (Online) 1865-0473
Published by Springer-Verlag Homepage  [2658 journals]
  • Capability of an Elman Recurrent Neural Network for predicting the
           non-linear behavior of airborne pollutants

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      Abstract: In this work an Elman Recurrent Neural Network (a type of Simple Recurrent Neural Network) is used for predicting the concentration of airborne pollutants O3, PM2.5 and PM10, which have a non-linear behavior, using data from Red Auto´ma´tica de Monitoreo Atmosfe´rico (RAMA), which is spreaded in the Zona Metropolitana del Valle de Me´xico (ZMVM). The study of PM10 and PM2.5 is important because, due to their tiny size, they can penetrate sensitive regions of respiratory system, among other important effects on human health, furthermore, it has been demonstrated that these have an important environmental impact. The study of ozone is important due its high toxicity. This pollutant has been responsible of several environmental contingences in Mexico City. An empirical method for imputing missing data using a series of linear regressions is proposed. A grid searching is used to find the best combination of some hyperparameters so that the variation of root-mean-square error between validation data and predicted data is minimized. A total of 144 experiments is developed measuring the validation root-mean-square error for each one, as well as root- mean-square error variation, in order to find the optimal combination. Two criteria are taken into account to evaluate the performance of network: root-mean-square error variation as mentioned before and evolution of metric values. This network showed a very good performance for ozone, with a maximum accuracy of 95.6 %, moderately good for PM2.5 with 46.4 and 28.6 % for PM10.
      PubDate: 2021-10-12
       
  • A comparison of various machine learning approaches performance for
           prediction suspended sediment load of river systems: a case study in
           Malaysia

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      Abstract: Accurate and reliable suspended sediment load (SSL) prediction models are necessary for the planning and management of water resource structures. In this study, four machine learning techniques, namely Gradient boost regression (GBT), Random Forest (RF), Support vector machine (SVM), and Artificial neural network ANN will be developed to predict SSL at the Rantau Panjang station on Johor River basin (JRB), Malaysia. Four evaluation criteria, including the Correlation Coefficient (R), Root Mean Square Error (RMSE), Nash Sutcliffe Efficiency (NSE) and Scatter Index (SI) will utilize to evaluating the performance of the proposed models. The obtained results revealed that all the proposed Machine Learning (ML) models showed superior prediction daily SSL performance. The comparative outcomes among models were carried out using the Taylor diagram. ANN model shows more reliable results than other models with R of 0.989, SI of 0.199, RMSE of 0.011053 and NSE of 0.979. A sensitivity analysis of the models to the input variables revealed that the absence of current day Suspended sediment load data SSLt-1 had the most effect on the SSL. Moreover, to examine validation of most accurate model we proposed divided data to 50% training, 25% testing and 25% validation) sets and ANN provided superior performance. Therefore, the proposed ANN approach is recommended as the most accurate model for SSL prediction.
      PubDate: 2021-10-08
       
  • Engineering application of fuzzy evaluation based on comprehensive weight
           in the selection of geophysical prospecting methods

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      Abstract: Faced with complex engineering geological problems, the application of comprehensive geophysical prospecting technologies allows for various technical achievements to complement each other, verify each other, reduce the ambiguity in geophysical prospecting results, and improve the accuracy of geophysical prospecting interpretations. At present, comprehensive geophysical prospecting is predominantly a simple synthesis of quantification, lacks effective intelligent decision-making methods, and cannot maintain pace with the development direction of future intelligent geophysical prospecting technologies. Therefore, this study proposes a geophysical prospecting selection evaluation method based on comprehensive weights to realize the transformation from empirical to scientific decision-making. In the proposed method, four criteria—specifically, detection accuracy, technical reliability, economic rationality, and data richness level—are first selected to establish an evaluation index system. Then, analytical hierarchy process and entropy weight method are used to combine subjective experience with objective data to form a comprehensive weight for the evaluation of geophysical prospecting selection through the fuzzy evaluation method. The efficacy of the proposed method was evaluated through application to karst exploration in the limestone mining area of the Hepu in Guangxi, for which an optimal geophysical prospecting scheme, composed of electrical resistivity tomography, microtremor survey method, and cross-hole resistivity computed tomography, was obtained. The scheme realizes the asymptotic detection of karst development from coarse to fine and improves the timeliness and economics of disaster management. These results verify the effectiveness and scientific soundness of the proposed method.
      PubDate: 2021-10-08
       
  • A review of downscaling methods of satellite-based precipitation estimates

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      Abstract: Satellite remote sensing is the main tool for estimating precipitation over areas with sparse rain gauge networks. Accurate gridded precipitation data at high temporal and spatial scales are needed for various studies such as hydrology, climatology, and meteorology. Meanwhile, downscaling of satellite precipitation products is necessary to attain such data because their spatial resolutions are too coarse for use in local region and basin scales or for parameterizing meteorological and hydrological models at a local scale. In recent years, plenty of attempts have been made to improve the resolutions of satellite-based precipitation estimates, and many algorithms have been proposed for this purpose. A review study of existing methods can help improve and develop future precipitation downscaling algorithms. Therefore, in this paper, the existing downscaling methods are reviewed, categorized, and summarized. Also, the performance of these methods in the studied regions is compared, and their advantages and limitations are highlighted. Finally, we concluded by stating the necessary considerations for future studies.
      PubDate: 2021-10-06
       
  • Framework for developing IDF curves using satellite precipitation: a case
           study using GPM-IMERG V6 data

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      Abstract: With the availability of satellite-based precipitation products, it is pertinent to develop methods to use these data products to design hydraulic structures. The satellite precipitation products play a vital role in ungauged locations or when information is required on a catchment scale. Before such applications, the accuracy and uncertainty associated with the products have to be investigated. In this study, we develop a framework that includes bias correction for the development of robust IDF curves. The framework is applied to a small region in the southeastern part of India, and the IDF curves were evaluated using the gauge data at nine locations. This study compares Intensity Duration Frequency (IDF) curves using the recent precipitation product Global Precipitation Measurement (GPM-IMERG V6) with ground-based gauge data. Results show that the spatial correlation between the satellite IDF and the gauge-based IDF improves significantly after bias correction, and the value is as high as 0.75 for 2–10 year return period. The bias between the satellite IDF and gauge IDF is low in the north part of the study region and is high in the southeastern part, prone to extreme rainfall. Further, a significant percentage of the satellite-based IDFs (with and without bias correction) lie inside the confidence interval of the gauge-based data. Thus, GPM V6 data have the potential to be used as an alternate data source for IDF generation in developing countries.
      PubDate: 2021-10-02
       
  • GEOstats: an excel-based data analysis program applying basic principles
           of statistics for geological studies

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      Abstract: Statistical evaluation of the data collected from field and laboratory is an important task in the earth sciences. The aim of a geological study is to reveal a scientific result from the earth, but the conclusions must be based on the analytical inferences, as in natural and engineering sciences. Therefore, the importance of data analysis increases depending on the improvement of technological methods in geology. The purpose of data analysis in geology is to examine the rate at which a feature changes within the population. The geological data may be lithological, textural (e.g. grain size and shape), structural (e.g. bedding, fault, foliation, jointing or lineation etc.) and chemical (e.g. major and trace elements, isotope ratios etc.) measurements of the rock, mineral, fossil, soil or water specimens. GEOstats is an excel-based data analysis program that provides graphical and numerical results, and data simulation/statistical modeling (e.g. simple regression analysis, box plot, Q–Q plot, XYZ plot, sample distribution and classification) of samples representing a population for geologists and other researchers as well. The program can perform both simple data analysis (e.g. basic statistical calculations) of numerical results and highly complex multivariate analysis such as cluster analysis, principal component analysis and common factor analysis . GEOstats is also able to carry out the error bars analysis by using relative standard deviation values for different confidence intervals.
      PubDate: 2021-10-02
       
  • Computer-assisted program for water Calco-Carbonic equilibrium computation

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      Abstract: The risk of scaling or corrosion of pipes and household appliances has attracted special interest from the part of drinking water supply systems designers. To address these deficiencies, the Calco-Carbonic balance in water must be accurately maintained and evaluated using either the graphic methods, appreciation indexes, or computer programs. In this work, we developed a computer-assisted software for the computation of the Calco-Carbonic equilibrium of water based on Legrand Poirier’s model. This software program, established in FORTRAN GNU with a graphical interface written with python using pyQt library pyqt5, provides two practical functions: evaluation of water Calco-Carbonic equilibrium numerically and graphically, and computation of the reagent rate required to make water neither aggressive nor encrusting. The program validation was carried out by comparing our results with those of the case considered by Legrand et al. (1981). In addition, the implementation of the program with two cases of water coming from reverse osmosis desalination plants of brackish water in the Sahara region and seawater in the Tipaza province shows for both stations, the technique of remineralization by carbonation is the best. Moreover, the results allowed us to choose between two remineralisations techniques among the eight techniques allowed applied in the case of brackish water desalination. It consists in adding lime and CO2 or infiltration on an uncalcined dolomite bed. In the case of seawater, we applied the same carbonation remineralisation technique where the final Ca2+ value was set at 8 °F (80 mg/lCaCO3). These techniques ensured a quality of produced water that complies with drinking water standards.
      PubDate: 2021-10-01
       
  • Characterization of hydrothermal alteration along geothermal wells using
           unsupervised machine-learning analysis of X-ray powder diffraction data

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      Abstract: Zonal distribution of hydrothermal alteration in and around geothermal fields is important for understanding the hydrothermal environment. In this study, we assessed the performance of three unsupervised classification algorithms—K-mean clustering, the Gaussian mixture model, and agglomerative clustering—in automated categorization of alteration minerals along wells. As quantitative data for classification, we focused on the quartz indices of alteration minerals obtained from rock cuttings, which were calculated from X-ray powder diffraction measurements. The classification algorithms were first examined by applying synthetic data and then applied to data on rock cuttings obtained from two wells in the Hachimantai geothermal field in Japan. Of the three algorithms, our results showed that the Gaussian mixture model provides classes that are reliable and relatively easy to interpret. Furthermore, an integrated interpretation of different classification results provided more detailed features buried within the quartz indices. Application to the Hachimantai geothermal field data showed that lithological boundaries underpin the data and revealed the lateral connection between wells. The method’s performance is underscored by its ability to interpret multi-component data related to quartz indices.
      PubDate: 2021-10-01
       
  • A comparative study of the cost–benefit strategy with the learning
           ensembles of decision stumps in polymetallic prospectivity modelling

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      Abstract: The prospecting cost–benefit strategy is an easy-to-implement mineral prospectivity modeling algorithm which uses the likelihood ratio, lift index and Youden index to represent the mineral potential. In this study, the prospecting cost–benefit strategy was extended to use the Matthews correlation coefficient (MCC) and F-measure to represent the mineral potential, and compared with the bagging and boosting ensembles of decision stumps in polymetallic prospectivity modeling in the Lalingzaohuo district (Qinghai Province, China). Replacing the decision trees with decision stumps in the bagging algorithm can alleviate the overfitting problem of the bagging ensemble model caused by the depth of the decision trees. According to the polymetallic prospectivity modeling results of the extended prospecting cost–benefit strategy, and bagging and boosting ensembles, seven mineral potential maps were produced, including likelihood ratio map, lift index map, Youden index map, MCC map, F-measure map, classification score maps. The receiver operating characteristic (ROC) curves show that the prospecting cost–benefit strategy is superior to the ensemble learning models in polymetallic prospectivity modeling. According to the seven mineral potential maps, polymetallic prospective areas were optimally delineated in the study area. These polymetallic prospective areas account for only a small percentage of the whole study area (12.61 – 16.95%) but contain almost all known polymetallic deposits (94 – 100%). Therefore, the MCC and F-measure can be used to represent the mineral potential in the prospecting cost–benefit strategy. The extended prospecting cost–benefit strategy performs better than the ensemble learning algorithms in polymetallic prospectivity modeling.
      PubDate: 2021-09-29
       
  • Optimized water depth retrieval using satellite imageries based on novel
           algorithms

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      Abstract: Bathymetry is a knowledge of water depth calculation, which is of great importance in many environmental management applications. The objective of this study is to improve the accuracy of the traditional ratio model as a widely used experimental bathymetry method. Therefore, firstly hybrid methods were proposed, which combined principal component analysis (PCA) and image fusion methods, to obtain more informative inputs for the Nayband bay bathymetry mapping under conditions of high turbidity. The results showed that the proposed hybrid bathymetry methods highly improved the accuracy of the depth maps. Then, two new algorithms, namely HybF_PSO and HybF_GA, have been introduced based on combining the proposed hybrid methods and the particle swarm optimization (PSO) or the genetic algorithm (GA) optimization methods. PSO and GA optimization methods were utilized to calculate the constant parameters of the depth model optimally. Compared to the traditional ratio model, the HybF_GA algorithm improved the bathymetry accuracy of depths shallower than − 2 m from 2.93 to 2.53, depths between − 2 and − 4 m from 3.2 to 1.56, depths between − 4 and − 8 m from 2.4 to 1.88, and areas deeper that − 8 m from 5.24 to 2.93. The HybF_PSO algorithm improved the accuracy of mapping areas deeper than − 8 m even more than the HybF_GA algorithm. Compared to the traditional ratio model, the HybF_PSO algorithm also highly improved the bathymetry accuracy in all the depth classes. Therefore, it can be concluded that the proposed bathymetry algorithms are very applicable and helpful.
      PubDate: 2021-09-24
       
  • Correction to: Application of fuzzy logic and neural networks for porosity
           analysis using well log data: an example from the Chanda Oil Field,
           Northwest Pakistan

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      PubDate: 2021-09-22
       
  • What is this article about' Generative summarization with the BERT
           model in the geosciences domain

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      Abstract: In recent years, a large amount of data has been accumulated, such as those recorded in geological journals and report literature, which contain a wealth of information, but these data have not been fully exploited or mined. Automatic information extraction offers an effective way to achieve new discoveries and pursue further analysis, which is of great significance for users, researchers or decision makers to aid and support analysis. In this paper, we utilize the bidirectional encoder representations from transformers (BERT) model, which is fine-tuned and then applied to automatically generate the title of a given input summarization based on the collection of published literature samples. The framework contains an encoder module, decoder module and training module. The core stages of summary generation involve the combination of encoder and decoder modules, and the multi-stage function is then used to connect modules, thus endowing the text summarization model with a multi-task learning architecture. Compared to other baseline models, our proposed model obtains the best results on the constructed dataset. Therefore, based on the proposed model, an automatic geological briefing generation platform is developed and used as an online platform to support the excavation of key areas and a visual presentation analysis of the literature.
      PubDate: 2021-09-22
       
  • BDS precise point positioning ambiguity resolution with high rate data and
           its application to seismic displacement and marine surveying

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      Abstract: Precise point positioning (PPP) with ambiguity resolution (AR) has been proved to be an effective method to improve the positioning accuracy and shorten the convergence time, which plays an important role in geodetic and geodynamic applications. In this study, the performance achieved based on the BeiDou Navigation Satellite System (BDS-2 and BDS-3) joint PPP-AR with high rate data was considered and the validation of its application to seismic displacement and marine high-precision surveying was evaluated. First, the methods of uncalibrated phase delays (UPDs) estimation and PPP-AR were introduced. Next, the performance achieved based on BDS PPP-AR in both static and simulated real-time kinematic mode was evaluated with hourly data selected from 16 tracking stations over 3 days and data sampling rate of 1 s. After convergence, the positioning accuracies in the east, north, and up directions were 3.4 cm, 1.5 cm, and 5.5 cm, which were improved by 11.9%, 3.8% and 2.2% compared with the float solutions. Finally, a test of applying BDS PPP-AR to marine surveying was carried out with two hours data collected from two independent GNSS receivers installed on a boat sailing along the coast of Bohai Sea, China. The onboard two data set are processed in post-processing kinematic BDS PPP mode. The accuracies were improved from 2.4 cm, 3.5 cm and 4.0 cm to 2.2 cm, 3.1 cm and 3.1 cm in the east, north and up directions by ambiguity resolution, with improvements of 8.3%, 11.4% and 22.5% over the float solutions. The results validated the feasibility of the BDS PPP-AR for high-accuracy maritime applications.
      PubDate: 2021-09-18
       
  • Prediction of urban water accumulation points and water accumulation
           process based on machine learning

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      Abstract: With the development of urbanization, global warming, rain island effect and other factors, cities around the world are facing more frequent and intense flood events. In order to deal with the damage caused by urban flood effectively, it is increasingly important to accurately predict and characterize the information of the flood in cities. In recent years, the rise of machine learning methods provides a new technical means for flood prediction. In this study, Naive Bayes (NB) and Random Forest (RF) algorithm were used to forecast the waterlogging point and the waterlogging process at the waterlogging point respectively to achieve the goal of predicting the whole process of urban waterlogging. Compared with the actual result, the four evaluation indexes (P, R, A and F1) of the NB classification models are 91%, 90.5%, 98.9% and 90.7% respectively, and the three regression indexes (MAE, MRER and RMSE) of the RF regression model were respectively 0.95%, 9.53% and 1.21%. The results demonstrated that the prediction result of NB model for waterlogging point is reliable, and the process of waterlogging predicted by RF model is also consistent with the actual situation, which verify the validity and applicability of the NB model and RF model. This research is expected to provide scientific guidance and theoretical support for urban flood disaster mitigation and relief work.
      PubDate: 2021-09-18
       
  • Correction to: What are the dominant influencing factors on the soil
           erosion evolution process in the Yellow River Basin'

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      PubDate: 2021-09-17
       
  • The seasonal and spatial distribution of hydrochemical characteristics of
           groundwater and its controlling factors in the eastern Loess Plateau

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      Abstract: Groundwater plays a key role in supplying water for drinking water, irrigation water, and industry water in the northern China. Recently, the availability and quality of groundwater resources in the eastern Loess Plateau (Shanxi province) have a serious impact on the agriculture, industry, and domestic sectors. This paper investigates the spatiotemporal variations of chemical and stable isotope composition of groundwater, and provides important information for the research of controlling factors of groundwater hydrochemical distribution in Shanxi province during two seasons. About 95 groundwater samples were collected from two seasons and measured the content of major ions and stable isotope, pH values, and total dissolved solids (TDS). The results showed that groundwater samples were mildly alkaline. Among all the groundwater samples, the HCO3− and Na+ dominated the total mass of the anions and cations, respectively. Significant seasonal and spatial variations can be observed in the TDS, deuterium (δ2H), and oxygen (δ18O) in groundwater samples. More pronounced variations of the groundwater TDS appeared in the quick-flow season with the highest TDS concentration observed at the central region and lower TDS values appeared in the northern and southern Shanxi. The groundwater samples mainly belong to the (HCO3−-Ca2+-Na+) type and the (HCO3−-SO42−-Ca2+-Na+) type. Rock weathering is the key controlling factor for the chemical composition of groundwater. In addition, nitrogen pollution of groundwater caused by human input is more significant in river valley basins such as the Yuncheng Basin, Linfen Basin, and Changzhi Basin. The significant influence of surface water-groundwater interaction for the groundwater can be observed at the valley basin in the central part of the Shanxi Province. The interaction between surface water and groundwater in the Linfen basin is especially remarkable.
      PubDate: 2021-09-17
       
  • Identification of specific wavelength regions for separating optically
           similar signals of coral reef benthic compositions

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      Abstract: The major problem to be overcome in mapping of coral reef ecosystem using remote sensing imagery is the confusion arises between optically similar spectral characteristics of different end-members which are to be used as input for various classification techniques. This work attempts to study in detail the possibilities of identifying the specific wavelength regions for separating optically similar signals of coral reef benthic compositions based on two different hypotheses using derivative analysis. First hypothesis is 1st order derivative analysis can be used to separate optical signatures of different families of corals; and second hypothesis is 2nd order derivative analysis can be used to separate optical signatures of coral species among Acropora family. Results imply that, i) at 515 nm Acropora Muricata, at 585 nm Favia Speciosa & Porites Solida and at 635 nm dead staghorn coral exhibit a negative first order derivative may be the evident that these spectral windows can be helpful in discrimination of corals based on family-wise; ii) at 558 nm Acropora Digitfera, at 565 nm , at 582 nm Acropora Secale, at 595 nm Acropora Varibalis, and at 598 nm Acropora Muricata exhibit a positive second order derivative can be helpful in separating different species among the Acropora family.
      PubDate: 2021-09-17
       
  • Correction to: Using hybrid artificial intelligence approach based on a
           neuro‑fuzzy system and evolutionary algorithms for modeling landslide
           susceptibility in East Azerbaijan Province, Iran

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      PubDate: 2021-09-14
      DOI: 10.1007/s12145-021-00704-4
       
  • Comprehensive framework for the integration and analysis of
           geo-environmental data for urban geohazards

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      Abstract: Geo-environmental information is an important basis for geohazard analysis and the integration of geo-environmental data is crucial in the construction of urban emergency management systems. In existing urban spatial information systems, the integration of geo-environmental data is neither intuitive nor efficient enough to support the analysis of geohazards well. On the basis of Web virtual globe, this paper proposes a comprehensive framework for the integration and analysis of geo-environmental data. This framework can effectively integrate geological data with a 3D geological model as a carrier, seamlessly connect geographic data, dynamically load real-time monitoring data, and build 3D visualisation and analysis scenes of urban full-space temporal information in the browser. The application example shows that the proposed framework can provide good geo-environmental data and practical data analysis functions for geohazard early warning and decision making, and improve the efficiency of government departments’ response to geohazards.
      PubDate: 2021-09-11
      DOI: 10.1007/s12145-021-00642-1
       
  • Risk Assessment of water inrush under an unconsolidated, confined aquifer:
           the application of GIS and information value model in the Qidong Coal
           Mine, China

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      Abstract: The mineable coal seam at Qidong coal mine, Huaibei coalfield, is adjacent to the overlying unconsolidated confined aquifer, which may induce water inrush hazards threatening the safe mining. This study presents an information value model (IVM) for the risk assessment of water inrush based on the information value and the geographic information system (GIS). In contrast to the general risk assessment model, this model was considered to improve the selection of the evaluation factor, which predicts the water inrush risk by using the best combination of factors. In general, the selection of the factors always had been decided by individual decision-makers. It was significantly subjective, which, in turn, make the prediction results quite different from the fact. Thus, it is of great significance to optimize the selection of evaluation factors before predicting the water inrush risk. This model was applied to the Qidong coal mine in North China. Then, the prediction results were further verified by the field distribution of water inrush, and the evaluation result is believed to be satisfactory. In addition, the AHP was also adopted for the risk assessment to compare with IVM. The AUC values of AHP and IVM without the optimization of factor selection are 0.6883 and 0.8229, respectively, and are 0.7253 and 0.8494 after the optimized selection, respectively. The results show that the IVM has a better prediction accuracy, and the prediction accuracy is increased after the optimization of factor selection, which indicates the IVM and the optimization could further help the future mining operation.
      PubDate: 2021-09-10
      DOI: 10.1007/s12145-021-00702-6
       
 
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