Applications of Big Data and Artificial Intelligence in Geoscience
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 January 2026 | Viewed by 687
Special Issue Editors
Interests: high performance computing; parallel computing; GPU; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: big data mineral resource prediction; mathematical geology; sedimentology
Interests: multi source data fusion; 3D visualization; big data analysis
Interests: computer networks; mobile networks; network routing; Internet-of-Things; service computing; fog computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to address the increasing demand for research on the application of artificial intelligence and data science in geoinformatics. Effectively processing and utilizing these ever-growing geoinformatics datasets presents numerous challenges, making it crucial to apply cutting-edge computing technologies to geoscience big data. The integration of artificial intelligence technologies, particularly those based on deep learning and big data, has opened new avenues for geoscience research. These technologies have been widely applied in various fields, including natural language processing and image recognition.
This Special Issue encourages researchers to explore innovative methods in AI and data science to solve complex problems in geoinformatics, including but not limited to the following sub-disciplines: remote sensing, geography, geology, and geophysics. These methods encompass improving or training statistical learning, machine learning, and deep learning algorithms applied to the analysis of text, images, geographic information systems (GIS), and other geoscience data. By focusing on these applications, we aim to address the computational challenges in geoinformatics more efficiently.
Topics of interest include, but are not limited to, the following:
- Data Mining in Geosciences;
- Machine Learning in Geographic Information Systems;
- Applications of Deep Learning in Earth Sciences;
- Geoscience Big Data Processing;
- Deep Learning for Geological Image Analysis;
- Geohazard Prediction and Management;
- Knowledge Graphs in Geoscience;
- Spatiotemporal Data Analysis in Geosciences;
- Environmental Monitoring and Intelligent Decision Support;
- Geological Data Visualization;
- Multisource Geoscience Data Fusion;
- Convolutional Neural Networks for Geological Image Recognition.
Dr. Yuzhu Wang
Dr. Xiaoping Mao
Dr. Junqiang Zhang
Prof. Dr. Zhangbing Zhou
Guest Editors
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Keywords
- geosciences
- geoinformatics
- machine learning
- deep learning
- artificial intelligence
- knowledge discovery
- knowledge graph
- large language model
- remote sensing
- spatial analysis
- environmental modeling
- geological data mining
- big data analysis
- big data processing
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