Found: 12
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Challenges of rainfall erosivity prediction: A Novel GIS-Based Optimization algorithm to reduce uncertainty in large country modeling.
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- Earth Science Informatics, 2024, v. 17, n. 1, p. 365, doi. 10.1007/s12145-023-01178-2
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- Article
Automatic extraction of urban objects from high-resolution aerial images using convolutional neural networks (Study area: Ahvaz city).
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- Advanced Applied Geology, 2023, v. 13, n. 2, p. 408, doi. 10.2205/AAG.2023.42422.2330
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- Article
Analysis of Groundwater Quality Spatial Distribution Pattern and Spatial Variations in Electrical Conductivity (Case Study: Hamadan Province).
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- Advanced Applied Geology, 2023, v. 12, n. 4, p. 747, doi. 10.22055/AAG.2022.39635.2271
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- Article
Applying optimum fusion method to improve lithological mapping of sedimentary rocks using sentinel-2 and ASTER satellite images.
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- Earth Science Informatics, 2022, v. 15, n. 3, p. 1765, doi. 10.1007/s12145-022-00836-1
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- Article
Increasing the accuracy of monthly and annual estimates of soil loss in Iran by considering the effect of snow cover in reducing rainfall erosivity.
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- Arabian Journal of Geosciences, 2022, v. 15, n. 15, p. 1, doi. 10.1007/s12517-022-10592-7
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- Article
Optimized water depth retrieval using satellite imageries based on novel algorithms.
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- Earth Science Informatics, 2022, v. 15, n. 1, p. 37, doi. 10.1007/s12145-021-00698-z
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- Article
Evaluating quality of surface water resources by ANN and ANFIS networks using Sentinel-2 satellite data.
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- Earth Science Informatics, 2022, v. 15, n. 1, p. 523, doi. 10.1007/s12145-021-00741-z
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- Article
Designing a conceptual model for geochemical geodatabase of oil wells: A case study of Gachsaran Oilfield.
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- Advanced Applied Geology, 2021, v. 11, n. 3, p. 616, doi. 10.22055/AAG.2020.34231.2137
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- Article
The natural resources potential assessing aimed at territorial planning using time-varying space data of vegetation index and LST.
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- Environmental Monitoring & Assessment, 2020, v. 192, n. 8, p. N.PAG, doi. 10.1007/s10661-020-08476-y
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- Article
Improved water quality mapping based on cross‐fusion of Sentinel‐2 and Landsat‐8 imageries.
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- IET Image Processing (Wiley-Blackwell), 2020, v. 14, n. 7, p. 1382, doi. 10.1049/iet-ipr.2019.1503
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- Article
Supervised cross-fusion method: a new triplet approach to fuse thermal, radar, and optical satellite data for land use classification.
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- Environmental Monitoring & Assessment, 2019, v. 191, n. 8, p. N.PAG, doi. 10.1007/s10661-019-7621-y
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- Article
Combined algorithm for improvement of fused radar and optical data classification accuracy.
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- Journal of Electronic Imaging, 2017, v. 26, n. 1, p. 1, doi. 10.1117/1.JEI.26.1.013017
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- Article