Artificial intelligence (AI) is one of the fastest growing disciplines in electronic information technology. Along with diversified data, AI-enabled technologies such as image processing, smart sensors, and intelligent inversion, are being tested by researchers in a wide variety of geosciences domains. These technologies have the potential to help geosciences move from qualitative to quantitative analysis. We believe that taking an interdisciplinary approach will deliver benefits to both geosciences and AI.

Artificial Intelligence in Geosciences is an open access journal providing an interdisciplinary forum where ideas and solutions related to artificial intelligence and its applications in geosciences can be shared and discussed. To support this discussion, we encourage authors to open source their code, data, and the labels used in AI.

We welcome both fundamental science and applied research describing the practical applications of AI methods in the fields of geology, rock physics, seismicity, hydrology, ecology, marine geosciences, planetary science, environment, volcanology, oceanography, remote sensing and GIS, and related areas.

Submissions to Artificial Intelligence in Geosciences may take the form of original research articles, review articles, perspective papers, or short communications, and a variety of topics will be considered. These include, but are not limited to:

• AI-based decision support systems

• AI-based precision geosciences

• Smart sensors and the Internet of Things

• Geosciences robotics and automation equipment

• Geosciences knowledge-based systems

• Computational intelligence in geosciences

• AI in geosciences optimization management

• Intelligent interfaces and human-machine interaction

• Machine vision and image/signal processing

• Machine learning and pattern recognition

• Neural networks, fuzzy systems, neuro-fuzzy systems

• Systems modeling and analysis

• Expert systems in geosciences

• Big data and cloud computing in geosciences

• Automatic navigation and self-driving technology

• High Performance Computing in the context of Machine Learning

Artificial Intelligence in Geosciences also welcomes suggestions and proposals for special issues.

Editorial Board