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portada Quantitative Geomorphology in the Artificial intelligence Era. Applications of AI for Earth and Environmental Change
Formato
Libro Físico
Editorial
Año
2025
N° páginas
558
Encuadernación
Tapa Blanda
Dimensiones
23.5x19.1 cm
ISBN13
9780443300363

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

Hamid Reza Pourghasemi;Narges Kariminejad (Autor) · Elsevier · Tapa Blanda

Quantitative Geomorphology in the Artificial intelligence Era. Applications of AI for Earth and Environmental Change - Hamid Reza Pourghasemi;Narges Kariminejad

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Reseña del libro "Quantitative Geomorphology in the Artificial intelligence Era. Applications of AI for Earth and Environmental Change"

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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