Integrative Sensing Strategies for Disaster Management
Will be published approx. on 12. June 2026
Book
Paperback/Softback
322 pages
978-0-443-27672-9 (ISBN)
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.
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.
More details
Series
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 229 mm
Width: 152 mm
Weight
1000 gr
ISBN-13
978-0-443-27672-9 (9780443276729)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Dr. Danlin Yu is a Professor at the Department of Earth and Environmental Studies, Montclair State University. Dr. Yu is a system dynamic modeler studying urban sustainability and environmental management. Dr. Yu's study specifically focuses on geographic information analysis, cartographical design and presentation, statistical analysis, urban and regional planning, and system dynamic modeling for complex systems (including environmental, urban, and regional systems). Dr. Yu has published widely in these fields for over 100 peer-reviewed articles in high-caliber journals with wide international circulation, and three collaborative books in the field of urban development and urbanization in China.
Charles Knoble is a Ph.D. Candidate at the Department of Earth and Environmental Studies, Montclair State University. Charles's research focuses on urban sustainable development and its impact on disadvantaged communities. More specifically, Charles is interested in using GIS and statistical analysis to identify the socioeconomic impacts sustainable development projects have on traditionally underserved communities.
Charles Knoble is a Ph.D. Candidate at the Department of Earth and Environmental Studies, Montclair State University. Charles's research focuses on urban sustainable development and its impact on disadvantaged communities. More specifically, Charles is interested in using GIS and statistical analysis to identify the socioeconomic impacts sustainable development projects have on traditionally underserved communities.
Content
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
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