Subjects -> ENVIRONMENTAL STUDIES (Total: 925 journals)
    - ENVIRONMENTAL STUDIES (822 journals)
    - POLLUTION (31 journals)
    - TOXICOLOGY AND ENVIRONMENTAL SAFETY (54 journals)
    - WASTE MANAGEMENT (18 journals)

ENVIRONMENTAL STUDIES (822 journals)                  1 2 3 4 5 | Last

Showing 1 - 200 of 378 Journals sorted alphabetically
ACS Chemical Health & Safety     Hybrid Journal   (Followers: 4)
ACS ES&T Engineering     Hybrid Journal   (Followers: 2)
Acta Brasiliensis     Open Access  
Acta Ecologica Sinica     Open Access   (Followers: 9)
Acta Environmentalica Universitatis Comenianae     Open Access  
Acta Limnologica Brasiliensia     Open Access   (Followers: 3)
Acta Oecologica     Hybrid Journal   (Followers: 11)
Acta Regionalia et Environmentalica     Open Access   (Followers: 1)
Advanced Electronic Materials     Hybrid Journal   (Followers: 5)
Advanced Energy and Sustainability Research     Open Access   (Followers: 4)
Advanced Sustainable Systems     Hybrid Journal   (Followers: 5)
Advances in Ecological Research     Full-text available via subscription   (Followers: 41)
Advances in Environmental Chemistry     Open Access   (Followers: 9)
Advances in Environmental Sciences - International Journal of the Bioflux Society     Open Access   (Followers: 12)
Advances in Environmental Technology     Open Access  
Advances in Life Science and Technology     Open Access   (Followers: 10)
Advances in Tropical Biodiversity and Environmental Sciences     Open Access   (Followers: 3)
Aeolian Research     Hybrid Journal   (Followers: 6)
African Journal of Environmental Science and Technology     Open Access   (Followers: 2)
Agricultura Tecnica     Open Access   (Followers: 1)
Agricultural & Environmental Letters     Open Access   (Followers: 3)
Agro-Science     Full-text available via subscription   (Followers: 1)
Agroecological journal     Open Access  
Agronomy for Sustainable Development     Open Access   (Followers: 18)
Agrosystems, Geosciences & Environment     Open Access   (Followers: 3)
Amazon's Research and Environmental Law     Open Access   (Followers: 2)
Ambiência     Open Access  
Ambiens. Revista Iberoamericana Universitaria en Ambiente, Sociedad y Sustentabilidad     Open Access  
American Journal of Energy and Environment     Open Access   (Followers: 4)
American Journal of Environmental Engineering     Open Access   (Followers: 6)
American Journal of Environmental Protection     Open Access   (Followers: 3)
American Journal of Environmental Sciences     Open Access   (Followers: 8)
American Naturalist     Full-text available via subscription   (Followers: 78)
Annals of Civil and Environmental Engineering     Open Access   (Followers: 1)
Annals of Environmental Science and Toxicology     Open Access   (Followers: 2)
Annals of GIS     Open Access   (Followers: 29)
Annual Review of Ecology, Evolution, and Systematics     Full-text available via subscription   (Followers: 80)
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: 36)
Annual Review of Resource Economics     Full-text available via subscription   (Followers: 9)
Applied and Environmental Soil Science     Open Access   (Followers: 14)
Applied Ecology and Environmental Sciences     Open Access   (Followers: 28)
Applied Environmental Education & Communication     Hybrid Journal   (Followers: 15)
Applied Journal of Environmental Engineering Science     Open Access   (Followers: 1)
Aquatic Ecology     Hybrid Journal   (Followers: 38)
Aquatic Toxicology     Hybrid Journal   (Followers: 23)
Arcada : Revista de conservación del patrimonio cultural     Open Access  
Architecture, Civil Engineering, Environment     Open Access   (Followers: 3)
Archives des Maladies Professionnelles et de l'Environnement     Full-text available via subscription  
Archives of Environmental and Occupational Health     Hybrid Journal   (Followers: 10)
Archives of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 12)
Archives of Environmental Protection     Open Access   (Followers: 3)
Archives of Toxicology     Hybrid Journal   (Followers: 20)
Arctic Environmental Research     Open Access  
Asian Journal of Environment & Ecology     Open Access  
Asian Journal of Rural Development     Open Access   (Followers: 9)
Asian Review of Environmental and Earth Sciences     Open Access   (Followers: 1)
ATBU Journal of Environmental Technology     Open Access   (Followers: 1)
Atmospheric and Climate Sciences     Open Access   (Followers: 32)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 2)
Augm Domus : Revista electrónica del Comité de Medio Ambiente de AUGM     Open Access  
Austral Ecology     Hybrid Journal   (Followers: 16)
Australasian Journal of Environmental Management     Hybrid Journal   (Followers: 8)
Australasian Journal of Human Security     Full-text available via subscription   (Followers: 1)
Australian Journal of Environmental Education     Full-text available via subscription   (Followers: 9)
Basic & Clinical Pharmacology & Toxicology     Hybrid Journal   (Followers: 13)
Basic and Applied Ecology     Hybrid Journal   (Followers: 21)
Behavioral Ecology     Hybrid Journal   (Followers: 56)
Behavioral Ecology and Sociobiology     Hybrid Journal   (Followers: 35)
Biocenosis     Open Access  
Biochar     Hybrid Journal   (Followers: 1)
Biodegradation     Hybrid Journal   (Followers: 2)
Biodiversity     Hybrid Journal   (Followers: 23)
Biofouling: The Journal of Bioadhesion and Biofilm Research     Hybrid Journal   (Followers: 2)
Bioremediation Journal     Hybrid Journal   (Followers: 4)
BioRisk     Open Access   (Followers: 2)
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: 5)
Bothalia : African Biodiversity & Conservation     Open Access  
Built Environment     Full-text available via subscription   (Followers: 5)
Bulletin of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 10)
Bulletin of the American Meteorological Society     Open Access   (Followers: 60)
Bumi Lestari Journal of Environment     Open Access  
Canadian Journal of Earth Sciences     Hybrid Journal   (Followers: 21)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 51)
Canadian Journal of Soil Science     Full-text available via subscription   (Followers: 12)
Canadian Water Resources Journal     Hybrid Journal   (Followers: 18)
Capitalism Nature Socialism     Hybrid Journal   (Followers: 20)
Carbon Capture Science & Technology     Open Access   (Followers: 4)
Carbon Resources Conversion     Open Access   (Followers: 2)
Case Studies in Chemical and Environmental Engineering     Open Access  
Casopis Slezskeho Zemskeho Muzea - serie A - vedy prirodni     Open Access  
Cell Biology and Toxicology     Hybrid Journal   (Followers: 10)
Chain Reaction     Full-text available via subscription  
Challenges in Sustainability     Open Access   (Followers: 9)
Chemical Research in Toxicology     Hybrid Journal   (Followers: 22)
Chemico-Biological Interactions     Hybrid Journal   (Followers: 3)
Chemosphere     Hybrid Journal   (Followers: 15)
Child and Adolescent Mental Health     Hybrid Journal   (Followers: 66)
Ciencia, Ambiente y Clima     Open Access  
City and Environment Interactions     Open Access   (Followers: 2)
Civil and Environmental Engineering     Open Access   (Followers: 6)
Civil and Environmental Engineering Reports     Open Access   (Followers: 3)
Civil and Environmental Research     Open Access   (Followers: 15)
CLEAN - Soil, Air, Water     Hybrid Journal   (Followers: 17)
Clean Technologies and Environmental Policy     Hybrid Journal   (Followers: 4)
Cleaner Environmental Systems     Open Access   (Followers: 3)
Cleaner Production Letters     Hybrid Journal   (Followers: 4)
Cleanroom Technology     Full-text available via subscription   (Followers: 1)
Climate and Energy     Full-text available via subscription   (Followers: 5)
Climate Change Ecology     Open Access   (Followers: 9)
Climate Change Economics     Hybrid Journal   (Followers: 35)
Climate Policy     Hybrid Journal   (Followers: 45)
Climate Resilience and Sustainability     Open Access   (Followers: 18)
Coastal Engineering Journal     Hybrid Journal   (Followers: 7)
Cogent Environmental Science     Open Access  
Columbia Journal of Environmental Law     Open Access   (Followers: 12)
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Water, Energy, and Environmental Engineering     Open Access   (Followers: 5)
Conservation and Society     Open Access   (Followers: 12)
Conservation Letters     Open Access   (Followers: 48)
Conservation Science     Open Access   (Followers: 26)
Consilience : The Journal of Sustainable Development     Open Access   (Followers: 2)
Contemporary Problems of Ecology     Hybrid Journal   (Followers: 4)
Critical Reviews in Environmental Science and Technology     Hybrid Journal   (Followers: 11)
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: 21)
Culture, Agriculture, Food and Environment     Hybrid Journal   (Followers: 9)
Current Environmental Health Reports     Hybrid Journal   (Followers: 1)
Current Forestry Reports     Hybrid Journal   (Followers: 1)
Current Landscape Ecology Reports     Hybrid Journal   (Followers: 1)
Current Opinion in Environmental Science & Health     Hybrid Journal  
Current Opinion in Environmental Sustainability     Hybrid Journal   (Followers: 14)
Current Research in Ecological and Social Psychology     Open Access   (Followers: 4)
Current Research in Environmental Sustainability     Open Access   (Followers: 2)
Current Research in Green and Sustainable Chemistry     Open Access  
Current Research in Microbiology     Open Access   (Followers: 21)
Current Sustainable/Renewable Energy Reports     Hybrid Journal   (Followers: 7)
Die Bodenkultur : Journal of Land Management, Food and Environment     Open Access  
Disaster Prevention and Management     Hybrid Journal   (Followers: 29)
Discover Sustainability     Open Access   (Followers: 2)
disP - The Planning Review     Hybrid Journal   (Followers: 1)
Drug and Chemical Toxicology     Hybrid Journal   (Followers: 13)
Duke Environmental Law & Policy Forum     Open Access   (Followers: 7)
Dynamiques Environnementales     Open Access  
E3S Web of Conferences     Open Access  
Earth and Environmental Science Transactions of the Royal Society of Edinburgh     Hybrid Journal   (Followers: 5)
Earth Interactions     Open Access   (Followers: 11)
Earth Science Informatics     Hybrid Journal   (Followers: 5)
Earth System Governance     Open Access  
Earth System Science Data (ESSD)     Open Access   (Followers: 7)
Earth Systems and Environment     Hybrid Journal   (Followers: 2)
EchoGéo     Open Access  
Eco-Thinking     Open Access   (Followers: 2)
Ecocycles     Open Access   (Followers: 4)
Ecohydrology     Hybrid Journal   (Followers: 8)
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: 134)
Ecological Chemistry and Engineering S     Open Access   (Followers: 2)
Ecological Complexity     Hybrid Journal   (Followers: 7)
Ecological Engineering     Hybrid Journal   (Followers: 4)
Ecological Indicators     Hybrid Journal   (Followers: 20)
Ecological Informatics     Hybrid Journal   (Followers: 3)
Ecological Management & Restoration     Hybrid Journal   (Followers: 15)
Ecological Modelling     Hybrid Journal   (Followers: 69)
Ecological Monographs     Full-text available via subscription   (Followers: 36)
Ecological Processes     Open Access   (Followers: 2)
Ecological Questions     Open Access   (Followers: 4)
Ecological Research     Hybrid Journal   (Followers: 10)
Ecological Restoration     Full-text available via subscription   (Followers: 21)
Ecologist, The     Full-text available via subscription   (Followers: 22)
Ecology     Full-text available via subscription   (Followers: 337)
Ecology and Evolution     Open Access   (Followers: 89)
Ecology Letters     Hybrid Journal   (Followers: 236)
EcoMat : Functional Materials for Green Energy and Environment     Open Access  
Economics and Policy of Energy and the Environment     Full-text available via subscription   (Followers: 13)
Économie rurale     Open Access   (Followers: 3)
Ecoprint : An International Journal of Ecology     Open Access   (Followers: 4)
Ecopsychology     Hybrid Journal   (Followers: 7)
Ecosphere     Open Access   (Followers: 8)
Ecosystem Services     Hybrid Journal   (Followers: 7)
Ecosystems     Hybrid Journal   (Followers: 31)
Ecosystems and People     Open Access   (Followers: 2)
Ecotoxicology     Hybrid Journal   (Followers: 9)
Ecotoxicology and Environmental Safety     Hybrid Journal   (Followers: 10)
Ecotrophic : Journal of Environmental Science     Open Access  
Ecozon@ : European Journal of Literature, Culture and Environment     Open Access   (Followers: 4)
Éducation relative à l'environnement     Open Access  
Electronic Green Journal     Open Access   (Followers: 4)
Empowering Sustainability International Journal     Open Access   (Followers: 5)
Energy & Environment     Hybrid Journal   (Followers: 23)
Energy & Environmental Science     Hybrid Journal   (Followers: 32)
Energy and Climate Change     Hybrid Journal   (Followers: 7)
Energy and Environment Focus     Free   (Followers: 7)

        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  [2484 journals]
  • Methods for landslide detection based on lightweight YOLOv4 convolutional
           neural network

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      Abstract: The rapid and accurate positioning of the landslides through remote sensing data plays an important role in post-disaster emergency rescue. This paper was proposed a new algorithm for landslide detection in the plateau environment. The YOLOv4 was used as the basic framework, and the MobileNetv3 model was utilized as the feature extraction network to replace the backbone neural network CSPdarknet53 which was to improve the efficiency of landslide detection. By applying depth separable convolution, the parameters of the model are decreasing significantly. To further improve the accuracy of landslide detection, the coordinate attention mechanism was introduced in the bottleneck. 3070 landslide images in the Linzhi area from 2010 to 2019 were obtained through Google Earth to train and test the model. On this basis, we compared the detection speed and accuracy of other single-stage and two-stage target detection algorithms in landslide detection. Moreover, the performances of the model were analyzed under the different attention mechanisms. The results show that our model can reduce the number of parameters by 83.59% compared with the YOLOv4 model. The accuracy of landslide detection by the model is improved to 91.2%, and the detection rate reaches 35f/s. It means that the model proposed in this study would provide useful information and rapid detection for hazard assessment and emergency rescue.
      PubDate: 2022-01-15
       
  • Straw return and organic fertilizers instead of chemical fertilizers on
           growth, yield and quality of rice

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      Abstract: Excessive nitrogen application, straw burning and lack of organic matter input have resulted in the decline of soil fertility and seriously threatened the sustainable production of high-quality Japonica Rice in Jilin Province. In order to clarify the effect of straw returning and replacement of chemical fertilizer with organic fertilizer on yield and quality of rice. Compared with chemical fertilization management of local farmers (CK), straw returning (SR) and replacement of chemical fertilizer with organic fertilizer (OF) were carried out respectively, and the growth characters, yield, quality and economic benefits were analyzed and compared. The results showed: compared with the CK, the plants of SR and OF grew more vigorously and yield increased by 12.0% and 12.4% respectively.SR and OF reduced the absorption of nitrogen fertilizer, reduced the protein content, and thus improved the eating quality. However, SR reduced the processing and appearance quality of rice. The profit of SR and OF increased by 2566 yuan/ha and 3209 yuan/ha, respectively due to the increase of yield. In conclusion, the research showed that the yield and profit of rice could be increased by straw returning to the field and replacement of chemical fertilizer with organic fertilizer, and to some extent, the rice quality can be improved.
      PubDate: 2022-01-14
       
  • A general characterization of representing spatiotemporal data and
           determining topological relations based on OWL

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      Abstract: With the popularization of mobile Internet and the continuous improvement of automation, the huge amount of data and information that WWW (World Wide Web) can contain is in an exponential explosive growth trend. OWL (Web Ontology Language) is the official WWW Ontology Language recommended by W3C and is extended by RDF and RDFS. It has strong semantic representation and description ability and is widely used in Semantic Web. However, because most real-life instances have temporal and spatial attributes, the original OWL language, which lacks the ability to express temporal and spatial attributes, no longer has good semantic representation ability. To solve the problem, we fuse the spatiotemporal attributes of the existing OWL conceptual triples and propose the methods for representing spatiotemporal data. Then we define spatiotemporal OWL class relationships and spatiotemporal extended OWL class relationships which mainly based on the fusion of spatiotemporal attributes. To better explain the definitions, we give some examples to illustrate the use of definitions in instances. Our definitions fuse spatiotemporal attributes into each element of the triples, and solve the problem that the previous definitions ignore that each element in triples has spatiotemporal attribute. These definitions make the relationship between classes more comprehensive, and make the model more applicable to spatiotemporal data.
      PubDate: 2022-01-13
       
  • Text visualization for geological hazard documents via text mining and
           natural language processing

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      Abstract: An increasing number of geological hazard documents about the mechanism and occurrence process of geological disasters contain unstructured geoscientific data that are not fully utilized. Text mining and visualization techniques offer opportunities to leverage this wealth of data and extract valuable information from dense, abstract geological disaster reports to quickly focus on the core information in geological reports and improve the efficiency of report usage. In this research, a flow framework for the automatic extraction of key information and its transformation to a simple and intuitive form for managers/researchers to quickly navigate, understand and make more informed decisions based on the key information are described. To automatically extract key information from text, an optimized term frequency-inverse document frequency algorithm is proposed to analyze text characteristics. The important information extracted from a case study document is demonstrated using a word cloud. Co-occurrence network analysis is used to present key content from geological reports and describe the correlations between words. We use the dependency grammar technique to extract triads of geological report text information and we visualize them using knowledge graphs. The results show that text visualization analysis can be used to identify the types and locations of geological disasters in reports, highlight key information from survey reports as an auxiliary public resource, and more rapidly analyze the key contents of a large number of geological disaster survey reports.
      PubDate: 2022-01-13
       
  • Analysis of Influence Mechanism of Spatial Distribution of Incoming Solar
           Radiation Based on DEM

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      Abstract: When using high-resolution satellite remote sensing data to estimate incoming solar radiation, the influence of complex topography must be taken into account. Elevation, land cover, slope and aspect are the controlling factors that affect the spatial distribution of incoming solar radiation. How can we quantify the above factors influence degree' Studying the influence mechanism on the spatial distribution of incoming solar radiation and using remote sensing inversion method and geographic detector for quantitative analysis can provide a scientific basis for the study of incoming solar radiation in complex topography. The remote sensing quantitative inversion method was used to retrieve the incoming solar radiation in the river valley area, and to obtain the spatial distribution of incoming solar radiation in the study area. At the same time, geographical detector was used to quantify the factors affecting the spatial distribution of incoming solar radiation, quantitatively analyzed the influence of various factors on incoming solar radiation, and thoroughly analyzed the influence mechanism factors on its spatial distribution through interaction. The results are as follows: (1) There is a good correlation between the inversion value and the observed value, the average relative error is 4.5%; (2) The distribution of incoming solar radiation has a strong topographic law; (3) The incoming solar radiation decreases with the increase of slope; (4) The incoming solar radiation tends to increase with the increase of elevation. According to the analysis results of geographic detector, in different periods, the influence degree of aspect on the spatial distribution of incoming solar radiation was 0.6940, 0.5661, 0.3368, 0.2646, 0.5929, 0.6562 and 0.6964 respectively, the influence degree of slope was 0.1242, 0.2900, 0.6339, 0.7214, 0.2846, 0.1861 and 0.1252 respectively, the influence degree of land cover was no more than 0.2465, and elevation has the least influence degree, not exceeding 0.0423.
      PubDate: 2022-01-12
       
  • A method for estimating the probability of glacial lake outburst floods
           based on logistic regression and geodetector: a case study of the
           Himalayan region

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      Abstract: Glacial lake is an important water resource. But glacial lake outburst floods (GLOFs) are destructive not only to property and infrastructure but also to people living in the regions. GLOFs prediction and risk evaluation are critical for preventing and mitigating the negative impacts. This paper proposes a prediction model for the possibility of GLOFs, which emphasizes the selection of easily available predictors. Taking 29 glacial lakes in the Himalayas as samples, the Geodetector is used to detect 4 selected predictors: the width of dam crest, the ratio of freeboard to dam height, the area of glacial lake and the area of mother glacier. The result shows the ratio of freeboard to dam height has the largest q-value of 0.3229. In the interaction detector, the width of dam crest and the ratio of freeboard to dam height had the highest explanatory power of 0.7667 after the interaction. The GLOFs probability prediction model correctly classifies 78% of drained lakes and 90% of undrained lakes, for an overall accuracy of 86%. Taking Amazhibu Tsho as an example, calculate variation in the probability of GLOF with different predictors. The results can provide practical and efficient references for local government and people.
      PubDate: 2022-01-12
       
  • Application of TOPSIS water abundance comprehensive evaluation method for
           karst aquifers in a lead zinc mine, China

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      Abstract: This paper presents a water abundance evaluation method based on improved fuzzy analytic hierarchy process (IFAHP) and entropy weight method (EWM) to solve the problem of unclear water abundance of karst aquifer in deep ore body mining. Taking the Maoping lead zinc mine in the southwest China as the research area, seven water abundance evaluation factors were selected to construct factor evaluation system. Then, comprehensive weights of evaluation factors were determined by game theory. Finally, a technique for order preference by similarity to an ideal solution (TOPSIS) water abundance evaluation model was established to identify water abundance zones with geographic information system (GIS). The results show that the weights determined by the iterated IFAHP, reflecting the mutual importance of the actual evaluation factors, enhances the accuracy of the subjective weights of the evaluation factors; the subjective and objective weight coefficients of evaluation factors determined by the game theory improves the rationality of the comprehensive weight model; compared with the unit inflow method, the comprehensive weighted TOPSIS water abundance evaluation model divides the water abundance zoning map in more detail, with a better fitting effect with the actual water inrush points of the study area. Consequently, the TOPSIS water abundance evaluation model not only provides theoretical guidance for the evaluation of karst aquifer water abundance, but also has guiding significance for the mining planning of ore body under the condition of karst aquifer.
      PubDate: 2022-01-11
       
  • Forecasting urban water consumption using bayesian networks and gene
           expression programming

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      Abstract: Forecasting Urban Water Consumption (UWC) has a significant impress in efficient urban water management in rapidly growing cities in arid regions. Enhancing forecasting accuracy of UWC using novel models is a crucial requirement in order to the management of smart cities. In this study, Bayesian Networks (BN) is developed as a probabilistic model and compared to Gene Expression Programming (GEP) model as an evolutionary algorithm for forecasting UWC. The amount of current water consumption predicts future water consumption. The scenario with sunshine hours was added to the parameter set as the best scenario in both BN and GEP models based on comparison of Root Mean Square Error (0.11, 0.16), Mean Absolute Relative Error (0.02, 0.05), Max Root Error (0.26, 0.26), and Coefficient of determination (0.8, 0.7), respectively. The outcomes indicate that the BN model provided a more desirable efficiency compared to the GEP model. Furthermore, it can be concluded that the sunshine hour has a considerable influence on UWC, and the ability of the BN model is greatly enhanced by adding this predictor to forecast UWC in a city in an arid region with rapid population growth.
      PubDate: 2022-01-11
       
  • Hyperspectral image classification based on optimized convolutional neural
           networks with 3D stacked blocks

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      Abstract: 3D convolution can fully utilize the spectral-spatial characteristics of hyperspectral image (HSI), and stacked blocks with deep layers are capable of extracting hidden features and utilizing discriminant information for classification. Naturally, a 3D convolutional neural network (CNN) based on stacked blocks named SB-3D-CNN is presented for HSI classification. Moreover, the proposed network introduces the attention mechanism before the fully connected layer, which can filter out interfering information effectively. Then we optimized the architecture to obtain optimal results on three commonly used datasets of Indian Pines, Salinas and Pavia University. Experimental results demonstrate that the optimized architecture achieves better classification rates than related recent works. Because the classification accuracies on the three datasets have reached saturation, we transferred the optimized architecture to a more complex dataset adopting the airborne hyperspectral data, which obtains from Guangxi province in south China. The results show that the optimized architecture achieves superior classification accuracies compared with other state-of-the-art methods. These results also demonstrate the optimized SB-3D-CNN has the advantages of validity and portability to more complex data.
      PubDate: 2022-01-11
       
  • Real time deep learning framework to monitor social distancing using
           improved single shot detector based on overhead position

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      Abstract: The current COVID 19 halo infection has caused a severe catastrophe with its deadly spread. Despite the implementation of the vaccine, the severity of the infection has not diminished, and it has become stronger and more destructive. So, the only solution to protect ourselves from infection is social-distancing. Although social-distancing has been in practice for a long time, in most places it is not effectively followed, and it is very difficult to find out manually at all times whether people are following it or not. Therefore, we introduced a newly developed framework of deep-learning technique to automatically identify whether people maintain social-distancing or not using remote sensing top view images. Initially, we are detecting the context of image which includes information about the environment. Our detection model recognizes individuals using the boundary box. Then centroid is determined over every detected boundary box. By means of applying Euclidean distance, the pair range distances of the detected boundary box centroid are determined. To evaluate whether the distance measurement exceeds the minimum social distance limit, the violation threshold is established. We used Improved Single Shot Detector model for detecting a person over an image. Experiments are carried out on widely collected remote sensing images from various environments. Based on the object detection algorithm of deep learning, a variety of performance metrics are compared to evaluate the efficiency of the proposed model. Research outcome shows that, our proposed model outperforms well while recognize and detect a person in a well excellent way.
      PubDate: 2022-01-11
       
  • Numerical simulation to estimate the conductive thermal state model –
           Mexican EGS zones as study cases

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      Abstract: This research presents a 2D conductive thermal representation for geothermal systems through the development of a numerical model based on heat transfer equations using Fortran language and applying the Tri-Diagonal Matrix Algorithm as a numerical solver of the equations. This numerical model simulates the heat transfer between two geothermal wellbores, used as boundary conditions, and calculates the temperature distribution. In addition, the geometry and composition of the model are based on the stratigraphic columns of the wellbores. The effect of the scarcity of geothermal gradient measurements in geothermal prospects is reduced by using a 2D model that requires only information in two wellbores. After applying the numerical model to a Hot Dry Rock zone and a sedimentary basin, it was found that the validation and accuracy estimation of the temperature profiles showed a good correlation and coherence between the measured and the simulated values. These results suggested the use of this numerical model for the reliable description of the thermal state of the upper section of the geothermal prospect with a high correlation with the observed measurements. This model would be very useful for defining the isotherms shape when planning the exploitation of the geothermal resource. Finally, the practical use of this model was highlighted because it only requires the thermal logs and thermal conductivity configuration of only two exploration wellbores as the main input data.
      PubDate: 2022-01-11
       
  • Correction to: Identification of forest disturbance and estimation of
           forest age in subtropical mountainous areas based on Landsat time series
           data

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      PubDate: 2022-01-10
       
  • Extraction of temporal information from social media messages using the
           BERT model

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      Abstract: Temporal information extraction from social media messages is of critical importance to several geographical applications. Combined with the characteristics of temporal information descriptions in Chinese text, different time expression patterns formed by time unit combinations are summarized. A deep learning-based information extraction algorithm (named BERT-BiLSTM-CRF) for automatically extracting temporal information from social media messages is proposed. Based on the bidirectional long short-term memory-conditional random field (BiLSTM-CRF) model, the BERT (bidirectional encoder representations from transformers) pretrained language model was used to enhance the generalization ability of the word vector model to capture long-range contextual information; then, the trained word vector was input into the BiLSTM-CRF model for further training. The proposed model was then evaluated on the constructed corpus, a set of manually annotated Chinese texts from social media messages. Among the basic models, the BERT-BiLSTM-CRF achieved the highest average F1-score of 85%. The experimental results show that the proposed method outperforms the current state-of-the-art models.
      PubDate: 2022-01-10
       
  • A comparative study of threshold selection methods for change detection
           from very high-resolution remote sensing images

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      Abstract: The determination of the optimal change threshold is an essential step for very high-resolution (VHR) remote sensing change detection. Although a number of change threshold selection methods have been developed for various applications, no single method can be suitable for all cases. It is difficult for users to select an applicable change threshold selection method for their own purposes. To address this challenge, eight common-used change threshold selection methods were studied from their pros and cons as well as performance. First, a clear analysis of these eight threshold selection methods was presented from the perspective of their pros and cons. Second, four groups of comparative experiments were conducted using VHR remote sensing images from the perspectives of greyscale histogram distribution, scene complexity, greyscale histogram processing, and runtime, respectively. From the experimental results, it is clear that the Otsu method and the FST method are the highest accuracy method for detecting multi-temporal VHR remote sensing images. Considering the time cost, the FST method outperforms the Otsu method. This study could be helpful for researchers to select appropriate change threshold approach for various change detection applications.
      PubDate: 2022-01-09
       
  • Seismic Hazard Analysis from Deterministic Method Using Fuzzy Logic in
           Anzali Port

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      Abstract: The land of Iran due to being located on the orogenic belt Alpine-Himalayas, one of the seismic regions of the world, it has always suffered heavy damage from earthquakes. Seismic hazard analysis is the determination of the potential level of ground motion parameters that might be generated by future earthquakes. Due to the diversity of parameters which might influence the occurrence of earthquakes, seismic hazard analysis like many other issues in seismology is a complicated problem, hence, it creates inevitable uncertainties in consequences. Therefore, Fuzzy logic is a suitable tool which is used as a decision-making method to solve problems and to model uncertainties and ambiguities. In this study, seismic hazard analysis is performed based on fuzzy logic technique and deterministic method (FDSHA). Also, the three input parameters, the earthquake maximum magnitude (Mmax), source-to-site distance (R), and fault type (F) and peak ground acceleration (PGA) as the output parameter are defined as fuzzy sets. Membership functions for input and output parameters are determined based on the judgment of the expert and fuzzy rules for peak ground acceleration according to the input parameters and the judgment of the expert is defined. The study area is Anzali Port, which is located in the Alborz orogenic belt in northern Iran. The results of estimating deterministic seismic hazard using fuzzy system show that the peak ground acceleration in Anzali Port is 0.55 g which is obtained from seismic source with a maximum magnitude of 8 with a faulting mechanism oblique at a distance of 72 km from it. Also, the results obtained from seismic hazard analysis by a deterministic method based on fuzzy logic, are in good agreement with the results obtained from other methods for Anzali Port.
      PubDate: 2022-01-08
       
  • Analysis of positive correlation in magnitude and time measurement for
           earthquake using electric signals

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      Abstract: Earthquake Prediction has become a field of seismology concerned with the specification of time, location, and magnitude of earthquakes to take preventive measures that could help in worst-case scenarios, i.e., destruction of homes and lives. Short Term Earthquakes depends on anomalous events known as precursors that occur before an Earthquake. Precursors are considered a warning before an earthquake. This prediction system uses Earth’s Electric Field Signal (EEFS) from Athens, Pyrgos, and Hios. Some examples are Ground Uplifting, Tilting, Emission of Radon Gas, Radio Waves, Magnetic Waves, and Earth’s Electric. The EEFS can be considered a precursor to estimate the magnitude and time of a possible earthquake. A minute-by-minute reading of the Earth’s Electric Field was taken, and few computations, models like ANN, SVM-ANN, and SVM-KNN, were applied. Few other models were created to estimate the time and magnitude of the earthquake. To discover an ideal model, results are compared without any constraints such as overfitting. The paper presents directions for estimating time and is directing for researchers to analyze in multiple dimensions.
      PubDate: 2022-01-08
       
  • Applying different soft computing methods to predict mechanical properties
           of carbonate rocks based on petrographic and physical properties

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      Abstract: Mechanical properties of carbonate rocks (elasticity modulus (E) and uniaxial compressive strength (UCS)) are important properties in tunneling, rock excavation and rock drilling blasting. Determination of these parameters using testing rock cores is almost difficult due to the discontinuities presence and it requires well-prepared cylindrical core samples. In addition, the testing procedure is expensive and time consuming. Thus, indirect tests are often utilized to evaluate the mechanical properties. In this research, a new technique for data processing called support vector regression (SVR) improved by metaheuristic algorithms (harmony search (HS), grey wolf optimizer (GWO), cuckoo search (CS), dolphin echolocation (DE) and genetic algorithm (GA)) to estimate of mechanical properties of carbonate rocks from physical properties and petrographic characteristics is applied. The techniques were employed in an open access literature. (case study: Koohrang’s third tunnel path, Iran). In these techniques, petrographic characteristics (allochem percent, carbonate percent, dolomite percent and grain size) and physical properties (saturated unit weight (γsat), S-wave velocity (Vs), dry unit weight (γd), P wave velocity (Vp)) were used as the inputs, while the mechanical properties of carbonate rocks were the outputs. Different performance concepts were used to compare the prediction models performance. The outcomes obtained show that the SVR-HS technique has robust potential for the prediction of mechanical properties of carbonate rocks based on physical properties and petrographic characteristics with high accuracy.
      PubDate: 2022-01-08
       
  • Efficient weighted naive bayes classifiers to predict air quality index

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      Abstract: In the past few decades, there have been many environmental changes that have lead to deteriorating air quality influenced by number of criteria pollutants and the prevailing climatic conditions. These pollutants lead to respiratory problems and other environmental effects such as acid rain, greenhouse effect etc. Therefore, quality prediction of air quality has long served as prospective and practical study area that has received massive attention. In literature, Naive Bayes classifier based on independence and equal importance assumption has been used by many researchers for air quality prediction. However, these assumptions never hold practically. To fulfill this purpose, two classifiers based on Weighted Naive Bayes named as Covariance based Weighted Naive Bayes and Convergent Cross Mapping based Weighted Naive Bayes have been proposed in this study to predict the air quality index of Faridabad, Delhi and Gurugram in India. The findings of the experimental work conducted in this study showed that both the proposed weighted classifiers perform better than the traditional Naive Bayes, Support Vector Machines and Neural Network classifiers with respect to various performance metrics- accuracy, average precision, average recall, error rate and F1 score. Further, this study depicts that Covariance based Weighted Naive Bayes and Convergent Cross Mapping based Weighted Naive Bayes have an average accuracy of 83.6% and 82.12% respectively.
      PubDate: 2022-01-07
       
  • Three-dimensional hydrogeological modeling method and application based on
           TIN-GTP-TEN

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      Abstract: A hydrogeological model reveals the spatial structure of aquifers and aquicludes from the perspective of 3D space. A 3D hydrogeological model plays an important role in spatial decision making of groundwater resources and rational development and utilization of underground space. The refined 3D hydrogeological model is an important subject in hydrogeology and 3D geographic information system. A hybrid hydrogeological 3D modeling method TIN-GTP-TEN based on triangulated irregular network (TIN), generalized tri-prism (GTP), and tetrahedral network (TEN) is proposed. This method is used to overcome the shortcomings of current hydrogeological 3D modeling methods. Inverse distance weighted square interpolation is performed to encrypt the density of borehole data. Delaunay triangulation is conducted on the scattered points with an improved point-by-point insertion algorithm to generate the surface model of the aquifer and aquiclude. In the hydrogeological body, the GTP is constructed with a vertical connection. The GTP is divided into TEN. The 3D geological modeling is realized by taking the TEN as a basic voxel. A dynamic reconstruction method of the GTP topological relationship is proposed to realize complex spatial analysis operations, such as excavation of hydrogeological 3D model and cutting in any direction. This method completely depends on the vertices and the intersection points of the cutting plane and the GTP itself and does not need to add any auxiliary lines and points to the GTP. The retained polyhedra after cutting are reorganized into multiple TENs to support the multiple cutting of the GTP model. Therefore, based on the hydrogeological conditions of Nantong City, east coast of China, this study constructed the three-dimensional model of hydrogeological drilling and the three-dimensional model of aquifers and aquifuges. The rapid cutting of a single arbitrary section of the 3D hydrogeological model was realized, which greatly enhanced the intuitiveness and accuracy of geological analysis.
      PubDate: 2022-01-07
       
  • Disaggregator – a tool for the aggregation and disaggregation of
           spatial data

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      Abstract: This paper describes the Disaggregator tool, developed for the aggregation and disaggregation of spatial data. There exist several types of point data that need to be aggregated for more effective visualization. On the other hand, some statistical datasets are only available for larger areas; the disaggregation procedure can recalculate this data into smaller areas. All disaggregation methods are strongly dependent on auxiliary data, so many disaggregation approaches, including dasymetric mapping, have been discussed in the literature. At the same time, only a few software implementations exist. Their functionality is very limited (Intelligent Dasymetric Mapping Toolbox) or they use only one method (e.g. the areal interpolation method), or their development is no longer supported (QGIS Dasymetric plugin). Disaggregation methods involve a more complex procedure, which makes them harder to automate and program. Due to the lack of ready-to-use softwaresolutions, the Disaggregator tool for ArcGIS Pro was created and published on GitHub as freely available software. It offers several methods for aggregation and disaggregation of spatial data. The tool was tested on several statistical datasets in Czechia.
      PubDate: 2022-01-05
       
 
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