Predictive Models for the Development of Landslide Early Warning Systems
Will be published approx. on 1. November 2029
Book
Paperback/Softback
250 pages
978-0-323-95929-2 (ISBN)
Description
Predictive Models for the Development of Landslide Early Warning Systems details advanced techniques in implementing landslide early warning systems (LEWS). The book provides a comprehensive resource for practitioners by including different techniques and models in landslide early warning, their practical applications, and case studies. The modeling theory is provided in a detailed but succinct format, verified with onsite models for specific regions and scenarios for different types of landslides and triggering factors. The book covers four main topics, including monitoring, data acquisition, transmission and maintenance of the instruments; analysis and forecasting, forecasting methods, and warning/dissemination of understandable messages alerting.
The exportability of different models is discussed in detail and followed by practical demonstrations for expert researchers' as well as postgraduates' needs. The book offers in-depth, up-to-date best practices for implementing LEWS based on current effective systems, new technologies, and standard methodologies at global level.
The exportability of different models is discussed in detail and followed by practical demonstrations for expert researchers' as well as postgraduates' needs. The book offers in-depth, up-to-date best practices for implementing LEWS based on current effective systems, new technologies, and standard methodologies at global level.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Dimensions
Height: 229 mm
Width: 152 mm
Weight
450 gr
ISBN-13
978-0-323-95929-2 (9780323959292)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Professor Pradhan is a globally recognized expert in geospatial analytics and artificial intelligence applications in Earth and environmental sciences. Currently a Distinguished Professor at the University of Technology Sydney (UTS), Australia, he also leads the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS). With a PhD in GIS-based modeling, Prof. Pradhan has over two decades of experience in spatial data science, remote sensing, natural hazard modeling, and environmental monitoring. He has been listed among the world's top 2% scientists by Stanford University and received numerous international awards, including from IEEE and Elsevier. A Fellow of the Royal Geographical Society (FRGS), he also serves on editorial boards of several top-tier journals. His research integrates geospatial AI and deep learning for disaster risk reduction, land use planning, and sustainability.
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
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
Content
1. Landslide Inventory and landslide susceptibility modelling2. Empirical and statistical rainfall thresholds3. Seismically induced landslides: reconstruction and forecasting 4. Process based slope stability modelling5. Monitoring of unstable slopes and wireless communication6. Data processing techniques in landslide research regarding rainfall threshold definition, reconstruction and near real time forecasting of seismic data7. Numerical modelling of debris flows, mud flows and rockfalls8. Social and Economic Impact, and Policies of landslide early warning systems9. LEWS: Technological advancements and future scope