Geo-foundation models and UAV data for post flooding damage assessment in Mozambique
June 2026
Earth Observation (EO) systems combined with Artificial Intelligence (AI) techniques have significantly advanced in recent years. The emergence and success of foundational models (FMs), such as ChatGPT...
Scalable variational Gaussian process framework for implicit geological modelling and compositional grade interpolation
June 2026
Geological modelling and estimation of polymetallic ore grades require methods that simultaneously honour spatial heterogeneity, compositional constraints, and predictive uncertainty. We present a scalable...
Optimized LightGBM-based prediction of foundation bearing capacity on spatially variable Bolton sand
June 2026
This study examines the random bearing capacity factor (Nγran) of shallow foundations on spatially variable Bolton sand using random field theory, adaptive meshing technique, and finite element limit...
Stress release coefficient prediction of sandy-gravel soil by extra tree algorithms
June 2026
One of the most significant geotechnical issues that must be addressed during the dams' first impoundment phase is the collapse settling of embankment dams. Due to the fact that it leads dams to undergo...
An open benchmark dataset of synthetic seismic data and real swell noise for evaluating deep learning denoising models
June 2026
Recent advances in deep learning (DL) have been fostered by open benchmark datasets that allow reproducible and systematic evaluation of models. Despite the increasing adoption of DL methods in geophysics,...
Enhancing land cover semantic segmentation with convolutional block attention modules and deep supervision
June 2026
High-resolution land cover semantic segmentation is challenged by strong class imbalance, spatial fragmentation of minority classes, and the presence of fine-scale textures and sensor noise that can...
Research and insights into the impact of different sampling strategies on machine learning-based lithology identification using well logging data
June 2026
Lithology identification is a critical task in geological exploration and mineral resource development, where accurate classification plays a pivotal role in geological modeling and resource evaluation....
Efficient specialization of foundation vision models for urban land cover classification
June 2026
Rapid urban expansion poses significant challenges for land use planning, spanning infrastructure provision to environmental monitoring. Accurate and detailed classification of urban land cover (ULC)...
From linear regression to hybrid networks: A comparative evaluation to find the optimal drought forecasting model for Iran
June 2026
Accurate and timely drought forecasting is a strategic imperative for Iran's national security, given the escalating water crisis. This necessity has driven the scientific community toward leveraging...
GIS-based wildfire prediction model in Indonesia using stacking ensemble learning
June 2026
In Indonesia, wildfires have become an annual disaster that results in significant losses across various aspects of life, including ecological, social, and economic conditions. To minimize these losses,...
Deep learning with Fourier Neural Operators for sedimentary structure recognition
June 2026
Sedimentary structure classification is fundamental to facies interpretation, depositional environment reconstruction, and reservoir characterization. While Convolutional Neural Networks (CNNs) have...
Deep learning-based downscaling of ERA5-Land temperature to 250 m resolution over the Trentino–South Tyrol Alpine region
June 2026
High-resolution near-surface temperature data are essential in mountainous regions, where complex topography induces strong spatial and temporal variability. However, coarse-resolution reanalysis products...
Machine learning and ensemble learning models for groundwater potential mapping in a fractured basin: Case of the Azrou-Khenifra basin, central massif, Morocco
June 2026
Groundwater potential mapping (GWP) is essential for sustainable resource managmment, particlarly in semi-arid and data-scarce regions. This study aims to delineate groundwater potential zones in the...
Predicting undrained shear strength in marine sediments using a physics-informed neural network (PINN)
June 2026
Undrained shear strength (SU) is a key parameter for evaluating slope stability, offshore foundation design, and submarine geohazards in marine environments. Conventional methods for predicting SU often...
Recent advances and challenges of cement bond evaluation based on ultrasonic measurements in cased holes
March 2026
Cement bond quality evaluations are essential for assessing zonal isolation between formation strata, providing crucial information for ensuring environmental and ecological safety in oil and gas exploitation,...
Prediction of the soil–water retention curve of compacted clays using PSO–GA XGBoost
March 2026
Soil–water retention (SWR) is fundamental for understanding the hydro-mechanical behavior of unsaturated clay soils. The soil–water retention curve is typically obtained through extensive and costly...
Hierarchical machine learning for the automatic classification of surface deformation from SAR observations
March 2026
Ground deformation processes, such as landslides and subsidence, cause significant social, economic, and environmental impacts. This study aims to automatically classify ground deformation processes...
The Fossil Frontier: An answer to the 3-billion fossil question
March 2026
Microfossil analysis is important in subsurface mapping, for example to match strata between wells. This analysis is currently conducted by specialist geoscientists who manually investigate large numbers...
DTPP:An efficient depthwise separable TCN for seismic phase picking
March 2026
With the rapid development of artificial intelligence in seismology, various deep learning-based seismic phase picking models have emerged in recent years. However, existing models face challenges in...
An FCM-based microseismic phase arrival picking method and application
March 2026
Artificial intelligence-based methods for picking microseismic phase arrivals have been widely adopted. However, these methods are frequently challenged by complex and dynamic monitoring scenarios,...
Machine learning-driven permeability prediction in carbonates and sandstones using NMR relaxation data
March 2026
Nuclear Magnetic Resonance (NMR) has proven to be a powerful tool for in-situ permeability quantification however, it typically requires laboratory calibration, and its accuracy is strongly influenced...
Spatial mapping and modelling of soil organic carbon using random forest and remote sensing variables in part of Kaduna, Northern Nigeria
March 2026
Reliable and up-to-date digital soil data is crucial for achieving Sustainable Development Goal 13 (Climate Action) by enabling improved monitoring of soil carbon and land degradation, thereby supporting...
Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data: A case study in Luoping county, Yunnan, China
March 2026
Recent advancements in remote sensing technology have made it easier to detect surface faults. Deep learning, especially convolutional models, offers new potential for automatic fault detection from...
An adaptable hybrid method for lossless airborne lidar data compression
March 2026
Light Detection and Ranging (LIDAR) point clouds provide high precision spatial data but impose significant storage and transmission challenges, often exceeding one gigabyte per square kilometer. This...
