Artificial Intelligence in Remote Sensing for Disaster Management
eBook - PDF

Artificial Intelligence in Remote Sensing for Disaster Management

  1. 372 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Artificial Intelligence in Remote Sensing for Disaster Management

About this book

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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Yes, you can access Artificial Intelligence in Remote Sensing for Disaster Management by Neelam Dahiya,Gurwinder Singh,Sartajvir Singh,Apoorva Sharma in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Chapter 1 Introduction to Natural Hazards, Challenges, and Managing Strategies
  8. Chapter 2 Role of Remote Sensing for Emergency Response and Disaster Rehabilitation
  9. Chapter 3 Fundamentals of Disaster Management Using Remote Sensing
  10. Chapter 4 Remote Sensing for Monitoring of Disaster-Prone Region
  11. Chapter 5 Artificial Intelligence Tools in Disaster Risk Reduction and Emergency Management
  12. Chapter 6 AI Tools and Technologies in Disaster Risk Reduction and Management
  13. Chapter 7 AI-Based Landslide Susceptibility Evaluation
  14. Chapter 8 Navigating Risk: A Comprehensive Study of Landslide Susceptibility Mapping and Hazard Assessment
  15. Chapter 9 Application of Geospatial Technology for Disaster Risk Reduction Using Machine Learning Algorithm and OpenStreetMap in Batticaloa District, Eastern Province, Sri Lanka
  16. Chapter 10 Landslide Displacement Forecasting With AI Models
  17. Chapter 11 Estimation of Snow Avalanche Hazardous Zones With AI Models
  18. Chapter 12 Predicting and Understanding the Snow Avalanche Event
  19. Chapter 13 A Systematic Review on Challenges and Opportunities in Snow Avalanche Risk Assessment and Analysis
  20. Chapter 14 AI-Based Modeling of GLOF Process and Its Impact
  21. Chapter 15 A Systematic Review of the GLOF Susceptibility Assessment Techniques
  22. Chapter 16 Challenges of GLOF Estimation and Prediction
  23. Chapter 17 Real-Time Earthquake Monitoring with Remote Sensing and AI Technology
  24. Chapter 18 Enhancing Seismic-Events Identification and Analysis Using Machine Learning Approach
  25. References
  26. Index
  27. Also of Interest
  28. EULA