Recent Trends in Geospatial AI
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Geospatial research is facing both enormous new potential and challenges due to artificial intelligence (AI). Theoretical advances, large data, computer hardware, and high-performance computing platforms that enable the creation, training, and deployment of AI models in a reasonable amount of time are the main drivers of its rapid development. There have been notable developments in the field of geospatial AI, particularly in the areas of machine learning, deep learning, and the most recent advancements in AI technology in both academia. These advancements are transforming how spatial data is ...
Geospatial research is facing both enormous new potential and challenges due to artificial intelligence (AI). Theoretical advances, large data, computer hardware, and high-performance computing platforms that enable the creation, training, and deployment of AI models in a reasonable amount of time are the main drivers of its rapid development. There have been notable developments in the field of geospatial AI, particularly in the areas of machine learning, deep learning, and the most recent advancements in AI technology in both academia. These advancements are transforming how spatial data is analyzed and interpreted, enabling more accurate predictions, real-time mapping, and enhanced decision-making capabilities across various applications. Recent Trends in Geospatial AI discusses the emerging potentials, challenges, and trends in geospatial AI. It further explores innovative applications of geospatial AI across a variety of sectors. Covering topics such as data processing, internet of things (IoT), and traffic flow optimization, this book is an excellent resource for graduate and postgraduate students, researchers, academicians, practitioners, and more.
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