The role of artificial intelligence and IoT in prediction of earthquakes: Review
December 2024
Earthquakes are classified as one of the most devastating natural disasters that can have catastrophic effects on the environment, lives, and properties. There has been an increasing interest in the...
Optimizing zero-shot text-based segmentation of remote sensing imagery using SAM and Grounding DINO
June 2025
The use of AI technologies in remote sensing (RS) tasks has been the focus of many individuals in both the professional and academic domains. Having more accessible interfaces and tools that allow people...
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...
On the application of machine learning algorithms in predicting the permeability of oil reservoirs
December 2025
Permeability is one of the main oil reservoir characteristics. It affects potential oil production, well-completion technologies, the choice of enhanced oil recovery methods, and more. The methods used...
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...
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,...
Automatic description of rock thin sections: A web application
June 2025
The identification and characterization of rock types is a core activity in geology and related fields, including mining, petroleum, environmental science, industry, and construction. Traditionally,...
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...
Determination of future land use changes using remote sensing imagery and artificial neural network algorithm: A case study of Davao City, Philippines
December 2023
Land use and land cover (LULC) changes refer to alterations in land use or physical characteristics. These changes can be caused by human activities, such as urbanization, agriculture, and resource...
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...
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...
Reservoir evaluation using petrophysics informed machine learning: A case study
December 2024
We propose a novel machine learning approach to improve the formation evaluation from logs by integrating petrophysical information with neural networks using a loss function. The petrophysical information...
LatentPINNs: Generative physics-informed neural networks via a latent representation learning
June 2025
Physics-informed neural networks (PINNs) are promising to replace conventional mesh-based partial differential equation (PDE) solvers by offering more accurate and flexible PDE solutions. However, PINNs...
Water resource forecasting with machine learning and deep learning: A scientometric analysis
December 2024
Water prediction plays a crucial role in modern-day water resource management, encompassing both hydrological patterns and demand forecasts. To gain insights into its current focus, status, and emerging...
ASTER data processing and fusion for alteration minerals and silicification detection: Implications for cupriferous mineralization exploration in the western Anti-Atlas, Morocco
December 2024
Alteration minerals and silicification are typically associated with a variety of ore mineralizations and could be detected using multispectral remote sensing sensors as indicators for mineral exploration....
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...
Soil liquefaction assessment using machine learning
June 2025
Liquefaction is one of the prominent factors leading to damage to soil and structures. In this study, the relationship between liquefaction potential and soil parameters is determined by applying feature...
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...
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...
Self-supervised multi-stage deep learning network for seismic data denoising
June 2025
Seismic data denoising is a critical process usually applied at various stages of the seismic processing workflow, as our ability to mitigate noise in seismic data affects the quality of our subsequent...
Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces
June 2025
This study employed convolutional neural networks (CNNs) for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces. The image dataset...
A combined deep CNN-RNN network for rainfall-runoff modelling in Bardha Watershed, India
December 2024
In recent years, there has been a growing interest in using artificial intelligence (AI) for rainfall-runoff modelling, as it has shown promising adaptability in this context. The current study involved...
Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology
December 2024
Pore size analysis plays a pivotal role in unraveling reservoir behavior and its intricate relationship with confined fluids. Traditional methods for predicting pore size distribution (PSD), relying...
Explaining machine learning models trained to predict Copernicus DEM errors in different land cover environments
December 2025
Machine learning models are increasingly used to correct the vertical biases (mainly due to vegetation and buildings) in global Digital Elevation Models (DEMs), for downstream applications which need...
Comparison of the performance of gradient boost, linear regression, decision tree, and voting algorithms to separate geochemical anomalies areas in the fractal environment
December 2025
In this investigation, the Gradient Boosting (GB), Linear Regression (LR), Decision Tree (DT), and Voting algorithms were applied to predict the distribution pattern of Au geochemical data. Trace and...