The rapid advancement of Artificial Intelligence (AI) has significantly transformed research methodologies across scientific disciplines, including applied geosciences. The integration of AI techniques such as machine learning, deep learning, and data mining with geospatial technologies has enhanced the efficiency, accuracy, and predictive capability of geoscientific analysis. Applied geosciences deal with real-world issues related to natural resources, environmental management, natural hazards, climate change, and sustainable development. Traditional geoscientific approaches often face limitations in handling large, complex, and multi-dimensional datasets generated through remote sensing, Geographic Information Systems (GIS), and field surveys. In this context, AI provides powerful tools for data processing, pattern recognition, modelling, and decision support. This paper reviews the major applications of AI in applied geosciences, including remote sensing and GIS, natural hazard assessment, hydrology, environmental monitoring, and resource management. It also discusses the benefits, challenges, and future prospects of AI-driven geoscience research. The study highlights that AI has become an indispensable component of modern applied geosciences, offering new opportunities for sustainable planning and informed decision- making.
Fakir et al. (Thu,) studied this question.
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