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Quantitative Geomorphology in the Artificial intelligence Era : Applications of AI for Earth and Environmental Change

By: Hamid Reza Pourghasemi (Edited by) , Narges Kariminejad (Edited by)

Not yet Published

Ksh 33,700.00

Format: Paperback or Softback

ISBN-10: 0443300364

ISBN-13: 9780443300363

Publisher: Elsevier - Health Sciences Division

Imprint: Elsevier - Health Sciences Division

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Aug 1st, 2025

Publication Status: Forthcoming

Product extent: 410 Pages

Product Classification / Subject(s): Geology & the lithosphere
Artificial intelligence

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Quantitative Geomorphology in the Artificial Intelligence Era: Applications of AI for Earth and Environmental Change focuses on bridging the gaps in this emerging discipline, it delves into the complex interplay between landforms and the processes that shape them, offering innovative solutions through AI and data-driven methods. The book addresses the standards, quality assessment of data, spatial and temporal analysis tools, and rigorous validation techniques in geomorphology. It uses computational intelligence as a pivotal tool alongside GIS, remote sensing, and other advanced technologies. Readers will find a holistic resource that fosters collaboration and knowledge exchange among geological fields, aiming to address geomorphological challenges, hazards, and solutions. By harnessing AI, GIS, remote sensing, machine learning, and geophysical techniques, it offers new dimensions to existing assessment methods and techniques.
Quantitative Geomorphology in the Artificial Intelligence Era: Applications of AI for Earth and Environmental Change focuses on bridging the gaps in this emerging discipline, it delves into the complex interplay between landforms and the processes that shape them, offering innovative solutions through AI and data-driven methods. The book addresses the standards, quality assessment of data, spatial and temporal analysis tools, and rigorous validation techniques in geomorphology. It uses computational intelligence as a pivotal tool alongside GIS, remote sensing, and other advanced technologies. Readers will find a holistic resource that fosters collaboration and knowledge exchange among geological fields, aiming to address geomorphological challenges, hazards, and solutions. By harnessing AI, GIS, remote sensing, machine learning, and geophysical techniques, it offers new dimensions to existing assessment methods and techniques.

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