The Future Integration between Artificial Intelligence and Geographical Studies: A Developmental Vision
DOI:
https://doi.org/10.25130/jfa.conf.10.4.11Keywords:
Artificial intelligence, Geographical studies, GeoAI, GIS, Remote sensingAbstract
This research aims to explore the future dimensions of integration between artificial intelligence (AI) and geographical studies from a developmental perspective, as one of the modern scientific pathways capable of introducing a qualitative shift in geographical research methodologies. The study begins by addressing the conceptual framework of AI and geography, while clarifying the core characteristics that make AI an effective tool for analyzing spatial and temporal data and detecting complex patterns. It further highlights the theoretical foundations underlying this integration, including Tobler’s First Law of Geography, the Modifiable Areal Unit Problem (MAUP), and spatial non-stationarity, which represent essential cornerstones for any effective synergy between AI and geography.
The research then focuses on practical applications such as remote sensing, geographic information systems (GIS), predicting environmental and climatic changes, managing natural resources, disaster risk management, in addition to the role of AI in urban planning and smart cities. The study demonstrates that these applications significantly enhance the efficiency of geographical research and strengthen its contribution to decision-making.
Finally, the research presents a forward-looking developmental vision that emphasizes the importance of strengthening digital infrastructure, integrating AI into geographical education curricula, establishing specialized research laboratories, and promoting institutional and research collaboration.
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