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.
1. Chapter 1 Introduction to integrated sensing in disaster management - p. 1 2. Chapter 2 Fundamentals of traditional remote sensing technologies - p. 27 3. Chapter 3 Social data as a disaster management tool - p. 55 4. Chapter 4 Data integration and analysis - p. 79 5. Chapter 5 Implementing sensing technologies in disaster zones - p. 111 6. Chapter 6 Policy and ethical considerations of remote sensing of disasters - p. 135 7. Chapter 7 Air quality monitoring and alerting systems with satellite images and Google Trends data in New Jersey - p. 151 8. Chapter 8 Urban flooding and public engagement with optical and social sensing - p. 189 9. Chapter 9 Evaluation during COVID-19 pandemic in China—City-scale analysis with nighttime light data and Baidu search index - p. 229 10. Chapter 10 Lead exposure in urban environments—Integrating satellite images, social sensing, and system dynamics simulative models in Newark, NJ - p. 257 11. Chapter 11 Future directions and innovations - p. 279 12. Glossary - p. 293 13. Index - p. 301
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.
1. Chapter 1 Introduction to integrated sensing in disaster management - p. 1 2. Chapter 2 Fundamentals of traditional remote sensing technologies - p. 27 3. Chapter 3 Social data as a disaster management tool - p. 55 4. Chapter 4 Data integration and analysis - p. 79 5. Chapter 5 Implementing sensing technologies in disaster zones - p. 111 6. Chapter 6 Policy and ethical considerations of remote sensing of disasters - p. 135 7. Chapter 7 Air quality monitoring and alerting systems with satellite images and Google Trends data in New Jersey - p. 151 8. Chapter 8 Urban flooding and public engagement with optical and social sensing - p. 189 9. Chapter 9 Evaluation during COVID-19 pandemic in China—City-scale analysis with nighttime light data and Baidu search index - p. 229 10. Chapter 10 Lead exposure in urban environments—Integrating satellite images, social sensing, and system dynamics simulative models in Newark, NJ - p. 257 11. Chapter 11 Future directions and innovations - p. 279 12. Glossary - p. 293 13. Index - p. 301
