Artificial Intelligence in Remote Sensing for Disaster Management (eBook, ePUB)

Redaktion: Dahiya, Neelam; Sharma, Apoorva; Singh, Sartajvir; Singh, Gurwinder

• Format: ePub

Produktbeschreibung

Invest in Artificial Intelligence in Remote Sensing for Disaster Management to gain invaluable insights into cutting-edge AI technologies and their transformative role in effectively monitoring and managing natural disasters.

Artificial Intelligence in Remote Sensing for Disaster Management examines the involvement of advanced tools and technologies such as Artificial Intelligence in disaster management with remote sensing. Remote sensing offers cost-effective, quick assessments and responses to natural disasters. In the past few years, many advances have been made in the monitoring and mapping of natural disasters with the integration of AI in remote sensing. This volume focuses on AI-driven observations of various natural disasters including landslides, snow avalanches, flash floods, glacial lake outburst floods, and earthquakes. There is currently a need for sustainable development, near real-time monitoring, forecasting, prediction, and management of natural resources, flash floods, sea-ice melt, cyclones, forestry, and climate changes. This book will provide essential guidance regarding AI-driven algorithms specifically developed for disaster management to meet the requirements of emerging applications.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 510
• Erscheinungstermin: 28. Mai 2025
• Englisch
• ISBN-13: 9781394287208
• Artikelnr.: 74334725

Autorenporträt

Neelam Dahiya, PhD is an assistant professor in the Department of Computer Applications at Chitkara University, Punjab, India. She has authored over ten articles in international journals and filed more than ten patents with the Indian Patent Office, five of which were granted. She has also reviewed various articles for renowned journals and conferences. Her research interests include remote sensing, digital image processing, deep learning, and hyperspectral imaging. Gurwinder Singh, PhD is an associate professor at the Institute of Computing at Chandigarh University, India. He has internationally published over 35 articles, conference papers, and book chapters, as well as one patent. He also serves as a member of the International Society for Photogrammetry and Remote Sensing and the Indian Society of Remote Sensing. His research interests include remote sensing, digital image processing, agricultural land use classification, machine learning, and deep learning. Sartajvir Singh, PhD is a professor and the Associate Director for the University Institute of Engineering at Chandigarh University, Punjab, India. He has filed over 50 patents with the Indian Patent Office, with over half granted. He has authored over 50 articles in international journals and edited various proceedings for conferences and symposia in addition to serving as an editor for several international journals. His research interests include electronics, remote sensing, and digital image processing. Apoorva Sharma is a digital analyst and assistant professor in the Department of Computer Science and Engineering, Chandigarh University, Punjab, India. She has published three articles in internationally reputed journals and conferences and contributed to innovative wearable and geospatial technologies. Her research interests include remote sensing, digital image processing, agriculture and cryosphere studies, machine learning, and deep learning.

Inhaltsangabe

Preface xvii
1 Introduction to Natural Hazards, Challenges, and Managing Strategies 1
Puninder Kaur, Taruna Sharma, Jaswinder Singh and Neelam Dahiya
2 Role of Remote Sensing for Emergency Response and Disaster Rehabilitation
21
Mochamad Irwan Hariyono and Aptu Andy Kurniawan
3 Fundamentals of Disaster Management Using Remote Sensing 35
Garima and Narayan Vyas
4 Remote Sensing for Monitoring of Disaster-Prone Region 59
Navdeep Singh Sodhi and Sofia Singla
5 Artificial Intelligence Tools in Disaster Risk Reduction and Emergency
Management 79
Rupinder Singh, Manjinder Singh and Jaswinder Singh
6 AI Tools and Technologies in Disaster Risk Reduction and Management 99
Alisha Sinha and Laxmi Kant Sharma
7 AI-Based Landslide Susceptibility Evaluation 125
Amanpreet Singh and Payal Kaushal
8 Navigating Risk: A Comprehensive Study of Landslide Susceptibility
Mapping and Hazard Assessment 139
Gaurav Kumar Saini and Inderdeep Kaur
9 Application of Geospatial Technology for Disaster Risk Reduction Using
Machine Learning Algorithm and OpenStreetMap in Batticaloa District,
Eastern Province, Sri Lanka 161
Zahir I.L.M., Suthakaran S., Iyoob A.L., Nuskiya M.H.F. and Fowzul Ameer
M.L.
10 Landslide Displacement Forecasting With AI Models 185
Sangeetha Annam
11 Estimation of Snow Avalanche Hazardous Zones With AI Models 201
Rajinder Kaur, Sartajvir Singh and Ganesh Kumar Sethi
12 Predicting and Understanding the Snow Avalanche Event 213
Nitin Arora and Sakshi
13 A Systematic Review on Challenges and Opportunities in Snow Avalanche
Risk Assessment and Analysis 229
Apoorva Sharma, Bhavneet Kaur and Sartajvir Singh
14 AI-Based Modeling of GLOF Process and Its Impact 243
Jaswinder Singh, Rajwinder Kaur, Puninder Kaur and Rupinder Singh
15 A Systematic Review of the GLOF Susceptibility Assessment Techniques 271
Oushnik Banerjee, Anshu Kumari and Apoorva Shamra
16 Challenges of GLOF Estimation and Prediction 289
Neelam Dahiya, Sartajvir Singh and Puninder Kaur
17 Real-Time Earthquake Monitoring with Remote Sensing and AI Technology
303
Koushik Sundar, Narayan Vyas and Neha Bhati
18 Enhancing Seismic-Events Identification and Analysis Using Machine
Learning Approach 323
Gurwinder Singh, Harun and Tejinder Pal Singh
References 341
Index 343