Predictive Models for the Development of Landslide Early Warning Systems - Brossura

Brossura

ISBN 10: 0323959296 ISBN 13: 9780323959292

Casa editrice: Elsevier Science Ltd, 2029

Riassunto

Predictive Models for the Development of Landslide Early Warning Systems details advanced techniques in implementing landslide early warning systems (LEWS). It provides a comprehensive resource for practitioners including different techniques and models in landslide early warning, their practical applications, and case studies. The modelling theory is provided in a detailed but succinct format, verified with on-site models for specific regions and scenarios for different types of landslides and triggering factors. The book covers four main topics required for an efficient LEWS: monitoring, including data acquisition, transmission and maintenance of the instruments; analysis and forecasting, including forecasting methods; warning/dissemination of understandable messages alerting for the impending threat; and response. The exportability of different models is discussed in detail and followed by practical demonstrations for expert researchers’ as well as postgraduates’ needs.

Predictive Models for the Development of Landslide Early Warning Systems offers in-depth, up-to-date best practices for implementing LEWS, based on current effective systems, new technologies, and standard methodologies at global level. This allows readers to understand universal LEWS methodologies and applications for use in their own research and development, including the use of current practical Big Data techniques.

• Presents advanced computational techniques in developing and implementing landslide early warning systems
• Details landslide early warning systems for various types of landslides and at different regional scales, allowing readers to quickly correlate the theory and practical applications covered into real-world solutions
• Provides case studies of different landslide types and at different levels, from local to national scale
• Includes thorough detail on the application of different ‘Internet of Things’ based instruments for slope monitoring at different scales

Su questo libro

Informazioni sugli autori

Biswajeet Pradhan is a distinguished professor at UTS School of Civil and Environmental Engineering. He is an international expert in data-driven modelling and a pioneer in combining spatial modelling with statistical and machine learning models for natural hazard predictions including landslides. He has a track record of outstanding research outputs, with over 600 journal articles. He is a highly interdisciplinary researcher with publications across 12 areas, listed as having ‘Excellent’ international collaboration status. He has been a Highly Cited Researcher for five consecutive years (2016-2020) and ranks fifth in the field of Geological & Geoenvironmental Engineering.

Dr Neelima Satyam is currently Associate Professor and Head of the Department of Civil Engineering at IIT Indore. She is actively engaged in teaching, research and consultancy in the field of Geotechnical engineering.

Dr. Neelima has published over 150 papers in reputed journals and conferences. She is the Co-opted member of PAC Civil and Mechanical Engineering SERB, DST (2015-2018). She has been the Chairperson of the selection committee for MEXT Scholarships of Japan since 2015. Dr Satyam is a recipient of IEI Young Engineers Award 2011; BRNS Young Scientist Research Award 2011; AICTE Career award 2012; JSPS fellowship in 2013; Young Woman Engineer award from INWES in 2012 and CIDC Vishwakarma Award in 2021

Dalla quarta di copertina

Predictive Models for the Development of Landslide Early Warning Systems details advanced techniques in implementing landslide early warning systems (LEWS). It provides a comprehensive resource for practitioners including different techniques and models in landslide early warning, their practical applications, and case studies. The modelling theory is provided in a detailed but succinct format, verified with on-site models for specific regions and scenarios for different types of landslides and triggering factors. The book covers four main topics required for an efficient LEWS: monitoring, including data acquisition, transmission and maintenance of the instruments; analysis and forecasting, including forecasting methods; warning/dissemination of understandable messages alerting for the impending threat; and response. The exportability of different models is discussed in detail and followed by practical demonstrations for expert researchers’ as well as postgraduates’ needs.

Predictive Models for the Development of Landslide Early Warning Systems offers in-depth, up-to-date best practices for implementing LEWS, based on current effective systems, new technologies, and standard methodologies at global level. This allows readers to understand universal LEWS methodologies and applications for use in their own research and development, including the use of current practical Big Data techniques.

Dettagli dell?edizione

• Editore: Elsevier Science Ltd
• Data di pubblicazione: 2029
• Lingua: Inglese
• ISBN 10: 0323959296
• ISBN 13: 9780323959292
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 250
• Redattore: Pradhan Biswajeet, Satyam Neelima
• Contatto del produttore: non disponibile
• Persona responsabile: LSWR Group; b.criscuolo@lswr.it; ; Via Spadolini, 7; Milano; Italia