Synthetic Aperture Radar for Disaster Management: Bridging Science and Solutions

Empower your response to global climate extremes by mastering the transformative power of synthetic aperture radar technology with this essential guide to its role in disaster management.

As humanity navigates the escalating challenges of a rapidly changing world marked by intensifying climate extremes, environmental degradation, and urbanization, the demand to mitigate disasters and protect vulnerable communities has never been more urgent. This book is a critical resource at this pivotal juncture, uniting the frontiers of synthetic aperture radar technology with the pressing demands of disaster resilience. It illustrates how science, engineering, and policy can converge to build a safer, more sustainable future, offering a transformative lens through which to address the complex interplay of global vulnerabilities and technological innovation. Using a holistic exploration of synthetic aperture radar’s transformative role in disaster management, the book equips readers to harness this emerging technology for rapid disaster response, infrastructure recovery, and climate resilience.

Readers will find the volume:

• Explores the role of machine learning, deep learning, and multi-sensor data fusion in interpreting SAR data for real-time decision-making;
• Includes real-world case studies that demonstrate the effectiveness of SAR in disaster scenarios, bridging theory with actionable solutions;
• Combines radar technology, computational advancements, and policy frameworks to address the interdisciplinary challenges of disaster management;
• Covers the end-to-end workflow of SAR in disaster contexts, from data acquisition and processing to interpretation and decision-making.

Audience

Designed for professionals, researchers, and students in remote sensing, geoinformatics, earth observation, disaster management, environmental agencies, and geospatial intelligence.

Pooja Joshi, PhD is an Assistant Professor at Swami Rama Himalayan University, Dehradun, India, with more than 13 years of teaching and research experience in the field of computer science and engineering. She has published three books and numerous articles in international journals and conferences. Her areas of expertise include artificial intelligence, machine learning, cloud computing, remote sensing, and disaster management technologies. She is also a certified SAR Remote Sensing expert from IIRS–ISRO and actively contributes to interdisciplinary research connecting AI, Earth Observation, and Sustainable Development Goals.

Ashutosh Bhatt, PhD is an Associate Professor and the Head of the Department of Computer Science and Engineering at Swami Rama Himalayan University, Dehradun, India, with more than 12 years of teaching experience. He has published one book, one book chapter, three patents, and numerous research papers published in prestigious journals. His research spans diverse topics, from job scheduling in multi-cloud environments to energy-efficient technologies in green cloud computing.

Neelam Sharma, PhD is an Associate Professor at Banasthali Vidyapith, Rajasthan, India, specializing in machine learning and data mining. She has extensive research and teaching experience in areas such as intrusion detection systems, cloud computing, task scheduling, landslide susceptibility prediction, and intelligent computing techniques.

Kapil Joshi, PhD is an Associate Professor in the Department of Computer Science and Engineering in the Uttaranchal Institute of Technology, Uttaranchal University, India, with more than ten years of experience. He has published various patents, more than 400 research papers in reputed journals, and more than 20 books. His areas of interest include operating systems, computer networks, web technology, data structure, and Java.