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...
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,...
Remote sensing estimation of rice chlorophyll content based on UAV image feature selection and PSO-optimized ensemble learning
March 2026
Chlorophyll content is one crucial indicator of evaluating crop growth and physiological status. Rapid, accurate, and large-scale monitoring of chlorophyll content is vital for the precise diagnosis...
Explainable flood damage assessment using multi-atrous self-attention and vision-language integration
March 2026
Flood disasters triggered by excessive rainfall cause severe damage to infrastructure and pose significant risks to human life. Within the context of disaster management, accurately identifying affected...
Application of YOLOv11 deep learning model for classification and counting ice-rafted debris (IRD) in core sediments in the Arctic Ocean
March 2026
The classification and quantification of ice-rafted debris (IRD) in marine sediments are key to reconstructing glacial-interglacial dynamics and sediment provenance. However, traditional IRD analysis,...
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...
DeepSeg-based noise reduction algorithm trained on a hybrid synthetic dataset for signals from acoustic logging-while-drilling
March 2026
Acoustic logging-while-drilling (ALWD) enables real-time acoustic measurements during drilling operations. However, challenging downhole conditions introduce considerable noise into ALWD signals. This...
Seismic facies characterization: Integrated subsurface-outcrop analysis for complex depositional systems in northeast India
March 2026
Seismic facies analysis involves the interpretation of reflection patterns from seismic data to provide insights into subsurface sedimentary environments, depositional processes, and lithological variations,...
A data-driven approach to earthquake early warning: Multicomponent site-spectra prediction using deep neural networks
March 2026
This paper presents a hybrid deep learning framework for earthquake early warning (EEW) that leverages front-site observations to predict target-site spectral characteristics—specifically Fourier amplitude...
Fast sparse representation impedance inversion method based on online adaptive reservoir characterization
March 2026
Seismic impedance inversion is a key technique for extracting reservoir information from seismic data. Traditional model-driven inversion methods often prove inadequate when dealing with complex reservoirs,...
Enhancing model parameterization with linearly constrained deep generative network for ensemble-based history matching
March 2026
Ensemble-based data assimilation methods have been widely used for history matching in subsurface reservoir modeling, but struggle to handle the complex nonlinear and non-Gaussian behaviors prevalent...
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...
A hybrid unsupervised-supervised deep learning framework for sandstone thickness prediction from seismic data
March 2026
Accurate sandstone thickness prediction from seismic data is vital for reservoir characterization and well placement optimization. However, conventional deep learning methods are often hindered by inefficient...
Thank you reviewers!
Available online 13 January 2026
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...
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...
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...
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...
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...