Academic Journal
Q1Applied Computing and Geosciences
About Applied Computing and Geosciences
Applied Computing and Geosciences is a scholarly journal published by its listed publisher. SCImago 2025 lists it in Q1, with an SJR of 0.761 and H-index of 22.
Coverage: 2019-2026. Research categories: Computer Science (miscellaneous) (Q1); Geology (Q1).
Open-access policies and author information
Reported in the official DOAJ public CSV snapshot (2026-09-01), downloaded 2026-10-03. Record updated 2026-04-27. This snapshot does not establish today’s listing status or fee quotation.
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Source-backed journal facts
Topics in published research
Geochemistry and Geologic Mapping; Mineral Processing and Grinding; Seismic Imaging and Inversion Techniques; Soil Geostatistics and Mapping; Hydrocarbon exploration and reservoir analysis; Diverse Scientific and Economic Studies.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
ActSeisDAS: A Python-based edge framework for continuous active seismic DAS monitoring
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Kjersti Kvistad Dengerud, Øyvind Hansen Singsaas, Jo Eidsvik, Nadège Langet et al.
2026-12 · DOI: 10.1016/j.acags.2026.100411ENVIDDA: Environmental data discovery and access framework
David Martinez Casas, Andrea R. Presas, Manuel A. Regueiro, José R.R. Viqueira et al.
2026-12 · DOI: 10.1016/j.acags.2026.100409Bayesian updating with machine learning and geostatistics for posterior predictions of unconventional reservoir performance
D. Wang, J.T. Foster, Y. Lu, A. Thompson et al.
2026-12 · DOI: 10.1016/j.acags.2026.100408Identification of granitic pegmatites based on GF-5 hyperspectral data and LSTM-Transformer model
Zhong Li, Ziye Wang
2026-12 · DOI: 10.1016/j.acags.2026.100406pyFRESCO: An open-source Python framework for hyperspectral data-driven discovery in planetary geology
M. Baroni, B. Baschetti, A. Pisello, M. Massironi et al.
2026-12 · DOI: 10.1016/j.acags.2026.100396A physics-guided machine learning approach to screening spectral induced polarization measurements
Klaudio Peshtani, Addison Goeker, Hardik Gohel, Zoe Vincent et al.
2026-12 · DOI: 10.1016/j.acags.2026.100414A novel toolbox for accurate thalweg detection applied to the estimation of salt wedge intrusion length
Fabio Viola, Júlia Kaiser, Alessandro De Lorenzis, Giorgia Verri et al.
2026-12 · DOI: 10.1016/j.acags.2026.100412Deep learning driven horizon tracking with confidence
Wenhao Zheng, Rebecca Bell, Lluis Guasch, Carlos Cueto et al.
2026-12 · DOI: 10.1016/j.acags.2026.100400Shoreline kinematics in Libreville (Gabon) derived from very high spatial resolution (VHR) imagery using machine and deep learning techniques
Nina Manomba-Mbadinga, Simona Niculescu
2026-12 · DOI: 10.1016/j.acags.2026.100407Hybrid Conv-LSTM architecture with pelican-based hyperparameter tuning for precision spatiotemporal forecasting of environmental indicators
Abdol Rassoul Zarei
2026-09 · DOI: 10.1016/j.acags.2026.100367Soft computing techniques for the prediction of non-convergent behaviour in iron tailings considering compositional attributes
Ismail Adeniyi Okewale, Hendrik Grobler, Antoine F. Mulaba-Bafubiandi
2026-09 · DOI: 10.1016/j.acags.2026.100382A prior-guided self-supervised contrastive transformer network for sparse geochemical anomaly identification
Qing Guo, Long Cao, Xiangdong Liu, Ke Yang et al.
2026-09 · DOI: 10.1016/j.acags.2026.100391An LLM-based multi-agent system for geoscience legacy document processing, knowledge extraction and quality control
Jiyin Zhang, Weilin Chen, Chenhao Li, Xiaogang Ma et al.
2026-09 · DOI: 10.1016/j.acags.2026.100362Towards efficient 3D Gaussian Splatting reconstruction with PairVPR-based image selection: A glacier UAV case study
Sicheng Zhao, Arjun Pakrashi, Soumyabrata Dev
2026-09 · DOI: 10.1016/j.acags.2026.100378Editorial Board
2026-09 · DOI: 10.1016/j.acags.2026.100403Laser space weathering analog experiments for micrometeorite bombardment and the question of simulation time
Maximilian P. Reitze, Iris Weber, Thomas Heyer, Andreas Morlok et al.
2026-09 · DOI: 10.1016/j.acags.2026.100357Inversion method for LWD electromagnetic wave in high-resistivity formations based on GAN-enhanced XGBoost-BiLSTM-transformer
Xiao Liu, Jie Wang, Yuyang Qi, Jiaqi Xiao et al.
2026-09 · DOI: 10.1016/j.acags.2026.100383GeoCORK: An improved workflow for U-Pb geochronology data management
Kathryn Metcalf, Jarrod M. Burges
2026-09 · DOI: 10.1016/j.acags.2026.100364Boosting and hybrid machine learning for clay weight percentage estimation from XRD and well logs: North Cook Inlet field, Alaska
Abu Bakker Siddique, Sushmita Sarker Chnapa, Farheen Zaman, Khanum Popi et al.
2026-09 · DOI: 10.1016/j.acags.2026.100384Reviews
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October 2, 2026 at 9:01 pm
October 2, 2026