Cellular automata models for simulation and prediction of urban land use change: Development and prospects
December 2025
Rapid urbanization and land-use changes are placing immense pressure on resources, infrastructure, and environmental sustainability. To address these, accurate urban simulation models are essential...
Machine learning assisted estimation of total solids content of drilling fluids
December 2025
Characterization and optimization of physical and chemical properties of drilling fluids are critical for the efficiency and success of drilling operations. In particular, maintaining the optimal levels...
Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning
December 2025
Capillary pressure plays a crucial role in determining the spatial distribution of oil and gas, particularly in medium-to-low permeability reservoirs, where it is closely linked to the rock's pore structure...
Generating high-resolution climate data in the Andes using artificial intelligence: A lightweight alternative to the WRF model
December 2025
In weather forecasting, generating atmospheric variables for regions with complex topography, such as the Andean regions with peaks reaching 6500 m above sea level, poses significant challenges. Traditional...
Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts
December 2025
Foraminifera are shell-bearing microorganisms that are commonly found in marine deposits on the seabed. They are important indicators in many analyses, are used in climate change research, monitoring...
Quantification of greenhouse gas emissions from livestock using remote sensing & artificial intelligence
December 2025
Greenhouse gases (GHGs) from agriculture in Africa are among the world's fastest-growing emissions, with the livestock sector as the primary contributor. However, the methods for quantifying these emissions...
Prediction of groundwater level in Indonesian tropical peatland forest plantations using machine learning
December 2025
Maintaining high groundwater level (GWL) is important for preventing fires in peatlands. This study proposes GWL prediction using machine learning methods for forest plantations in Indonesian tropical...
Online learning to accelerate nonlinear PDE solvers: Applied to multiphase porous media flow
December 2025
We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase...
Earthquake location and magnitude estimation using seismic arrival times pattern and gradient boosted decision trees
December 2025
We present a machine learning approach for earthquake location and magnitude estimation based on seismic arrival time patterns, using Histogram-Based Gradient Boosting for its high accuracy and computational...
Machine learning applied to recognition of dinoflagellate cysts: Type study with the species Batioladiniumlongicornutum
December 2025
This study explores the application of YOLOv10, a cutting-edge object detection framework, to automate the identification and classification of Batioladinium longicornutum. Utilizing a dataset of 137...
Understanding hydrological responses through LULC analysis and predictive modelling (MLPNN-MC Model): A study of Bandu Sub-watershed (India) over three decades
December 2025
•Bandu sub-watershed in Purulia district was categorized into eight distinct LULC classes using Google Earth Engine.•Thirty years of decadal transformations (1992–2022) predicts future LULC scenarios...
Opportunities, epistemological assessment and potential risks of machine learning applications in volcano science
December 2025
This manuscript explores the opportunities and epistemological risks of using machine learning in the Earth sciences with a focus on igneous petrology and volcanology. It begins by highlighting the...
Application research of SSA-RF model in predicting the height of water-conducting fracture zone in deep and thick coal seams
December 2025
The 91 measured values of the development height of the water-conducting fracture zone (WCFZ) in deep and thick coal seam mining faces under thick loose layer conditions were collected. Five key characteristic...
Machine-learning seismic damage assessment model for building structures
December 2025
Buildings in seismic-prone regions are highly vulnerable to structural damage, necessitating meticulous Seismic Damage Assessment (SDA) for accurate design and mitigation strategies. The intricate nature...
Development of a reliable rock slope stability model utilizing field and analytical data – An integration of FE-ML approaches
December 2025
Slope instability in hilly regions is a highly complex phenomenon, with triggering factors ranging from natural events to anthropogenic activities. Such failures hit disastrous losses both in terms...
Unsupervised hierarchical sequence stratigraphy framework of carbonate successions
December 2025
Performing the high-resolution stratigraphic analysis may be challenging and time-consuming if one has to work with large datasets. Moreover, sedimentary records have signals of different frequencies...
Advancements in Sinkhole Remediation: Field data-driven Sinkhole grout volume prediction model via machine learning-based regression Analysis
December 2025
Sinkhole formation poses a significant geohazard in karst regions, where unpredictable subsurface erosion often necessitates costly grouting for stabilization. Accurate estimation of grout volume remains...
Undrained uplift capacity prediction of open-caisson anchors in anisotropic clays using XGBoost integrated with mutation-based genetic algorithms
December 2025
This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis (FELA) and a hybrid machine learning framework. The FELA simulations...
Quantifying uncertainty of mineral prediction using a novel Bayesian deep learning framework
December 2025
Mineral resource exploration increasingly demands not only accurate prospectivity maps but also reliable measures of confidence to guide high-stakes decisions. In this study, a novel Bayesian deep learning...
AI-based approaches for wetland mapping and classification: A review of current practices and future perspectives
December 2025
Wetlands are critical ecosystems that provide essential ecological, hydrological, and socio-economic services, such as water purification, climate regulation, and biodiversity conservation. However,...
Unveiling climate-driven water surface dynamics in the largest tropical lake in Borneo: A machine learning approach using multi-source satellite imagery
December 2025
Tropical lakes such as Lake Sentarum in Kalimantan, Indonesia, represent ecologically rich ecosystems with high biodiversity and constitute the largest lake on the island of Kalimantan. This lake serves...
Intelligent identification of fractures and holes in ultrasonic logging images based on the improved YOLOv8 model
December 2025
Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images, this paper integrates the YOLOv8 model with the Convolution Block Attention Module...
GeoNeXt: Efficient landslide mapping using a pre-trained ConvNeXt V2 encoder with a PSA-ASPP decoder
December 2025
Landslides constitute one of the most destructive geological hazards worldwide, causing thousands of casualties and billions in economic losses annually. To mitigate these risks, accurate and efficient...
Constructing regional mineral prospecting knowledge graph from GIS maps
December 2025
Geographic Information System (GIS) layers contain both spatial precision and domain knowledge, making them valuable for mineral prospectivity analysis. This study proposes a task-oriented methodology...
Identification of major minerals in igneous rock microscopic images from thin sections through deep neural network analysis
December 2025
Several socio-environmental needs (medicine, industry, engineering, orogenesis, genesis, etc.) require minerals to be more precisly defined and characterised. The identification of minerals plays a...