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11 articles for “Spatial Uncertainty”
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Advance in Spatial Statistics for Environmental Data Analysis
Abstract: Recent advancements in spatial statistics have significantly enhanced the analysis of environmental data, addressing complex spatial dependencies and offering robust methodologies for environmental monitoring, modeling, and decision-making. This abstract highlights key developments in the field, emphasizing their applications and impact. Geostatistical Methods, Improved geostatistical techniques, such as kriging and co-kriging, provide more accurate predictions of environmental variables by incorporating spatial correlation structures. Advanced kriging variants, including Bayesian kriging and machine …
Published in Research & Reviews : Journal of Statistics · Vol. 12, Issue 3, 2023 · pp. 35–39 Read article
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Geo-spatial Predictions of Soil Organic Carbon: A Review
Abstract: Soil Organic Carbon (SOC) plays an important role in conservation of biophysical environment, i.e., biogeochemical cycles, soil fertility, water quality, atmospheric carbon control, temperature control, sustainable land management and food production. Geo-statistical techniques can be useful for precise estimations and preparation of high quality SOC maps essential for planning and monitoring the biophysical environment. Several studies have used geo-statistical techniques successfully for description of spatial patterns, quantitative modeling, spatial predictions …
Published in Journal of Remote Sensing & GIS · Vol. 5, Issue 2, 2014 · pp. 23–39 Read article
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Climate Change and the Hydrologic Cycle: Emerging Patterns, Process Alterations, and Implications for Sustainable Water Resources Management
Abstract: Climate change is profoundly altering the global hydrologic cycle, affecting the movement, storage, and quality of water across atmospheric, terrestrial, and aquatic systems. Rising global temperatures, changing precipitation patterns, increasing atmospheric evaporative demand, and intensifying hydroclimatic extremes are reshaping key hydrological processes, including evapotranspiration, soil moisture dynamics, runoff generation, streamflow regimes, groundwater recharge, and water quality. This review synthesizes recent advances in understanding the impacts of climate change on the …
Published in International Journal of Atmosphere · Vol. 3, Issue 2, 2026 · pp. 34–54 Read article
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Seasonal Dynamics of Coastal Landscapes: A Critical Review Using Remote Sensing and GIS
Abstract: Coastal landscapes are among the most dynamic environments on Earth, undergoing continuous transformation due to both natural processes and anthropogenic activities. In India, particularly along the southern coastal regions of Andhra Pradesh, Tamil Nadu, and Kerala, shoreline morphology and sediment transport patterns are significantly influenced by seasonal monsoons, cyclones, storm surges, waves, tides, and changing river discharges. These factors contribute to varying rates of coastal erosion, accretion, inundation, and land- …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Reliability-Based Prediction of Bearing Capacity of Shallow Foundation Along Ajaokuta-Kaduna-Kano Pipeline Track
Abstract: This paper investigates the geotechnical properties and reliability-based bearing capacity predictions for shallow foundations along the proposed Ajaokuta-Kaduna-Kano (A-K-K) pipeline track in Nigeria. The variability of subsoil properties along this route poses significant challenges to ensuring foundation stability and safety, necessitating an in-depth study. A total of twenty boreholes were strategically drilled at key locations to a maximum depth of 30 meters, providing comprehensive subsurface profiles. Soil samples collected from …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 1, 2025 · pp. 9–17 Read article
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Fracture Analysis of Functionally Graded Material (FGM) Plates Using Extended Finite Element Method: A Review.
Abstract: Functionally Graded Materials (FGMs), have drawn a lot of interest in various engineering applications due to their superior mechanical properties and ability to withstand extreme conditions. Fracture analysis in FGMs focuses on understanding how cracks initiate and propagate within these complex materials. The stress distribution becomes irregular due to spatial property variations which produces different crack paths than what occurs in homogeneous materials. The examination of FGM plates under fracture …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 9–15 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article