Integrative Sensing Strategies for Disaster Management
Series: Earth Observation;
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67 569 Ft
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Product details:
- Publisher Elsevier
- Date of Publication 12 June 2026
- ISBN 9780443276729
- Binding Paperback
- No. of pages308 pages
- Size 276x216 mm
- Language English 700
Categories
Long description:
Integrative Sensing Strategies for Disaster Management explores the synergy between airborne remote sensing and social data in addressing disaster management. The book provides a framework for leveraging diverse data sources to enhance response and resilience. Detailed chapters cover the fundamentals of remote sensing, data integration techniques, and ethical implications, showcasing practical case studies in urban flooding, air quality monitoring, and pandemic evaluation. The book is an essential resource for postgraduates, PhD students, researchers, and professors in Earth observation and disaster management.
Users will find this book to be a great resource for advancing their understanding of integrated sensing technologies, including current challenges and emerging trends, and tactics on how to implement innovative solutions.
- Provides an integrated approach to remote sensing technologies, combining airborne remote sensing with social data analytics
- Offers readers a unique perspective on leveraging multiple geospatial data sources for enhanced disaster management and resilience
- Includes practical case studies that demonstrate the applications of integrated sensing technologies across a variety of areas
- Addresses the broader implications and responsibilities associated with using advanced sensing technologies in disaster management
Table of Contents:
1. Introduction to Integrated Sensing in Disaster Management
2. Fundamentals of Airborne Remote Sensing
3. Social Data as a Disaster Management Tool
4. Data Integration and Analysis
5. Implementing Sensing Technologies in Disaster Zones
6. Policy and Ethical Considerations of Remote Sensing of Disasters
7. Air Quality Monitoring and Alarming Systems with Satellite Images and Twitter Data in New Jersey
8. Urban Flooding and Public Engagement with Optical and Social Sensing
9. Evaluation During COVID19 Pandemic in China - City-Scale Analysis with Nighttime Light Data and Baidu Search Index
10. Lead Exposure in Urban Environments - Integrating Satellite Images, Social Sensing, and System Dynamics Simulative Models in Newark, NJ
11. Future Directions and Innovations
