Abstract
Geospatial artificial intelligence (GeoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning, data mining, and high-performance computing to extract knowledge from spatial big data. GeoAI, or geospatial artificial intelligence, has become an emerging topic and the frontier for spatial analytics in Geography. This study explores how these technologies can enhance spatial analysis and decision support systems, leading to more accurate, efficient, and sustainable outcomes. The integration of AI and Big Data facilitates improved data acquisition and management, enabling the processing of large volumes of geospatial data. The paper highlighted the applications of AI and Big Data in geography, such as optimizing urban development, environmental monitoring, and disaster management. However, it also acknowledges the challenges, including data privacy and security concerns, potential biases in algorithms, and data quality and integration issues. The paper concludes by emphasizing the need for interdisciplinary collaborations and the development of user-friendly tools and platforms to democratize the adoption of AI and Big Data applications in geography.
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