Ground Based Synthetic Aperture Radar

Motoyuki Sato, Weike Feng, Yuta Izumi, Amila Karunathilake

Ground Based Synthetic Aperture Radar
Format
Hardback
Publisher
Taylor & Francis Ltd
Country
United Kingdom
Published
30 December 2024
Pages
294
ISBN
9781032327068

Ground Based Synthetic Aperture Radar

Motoyuki Sato, Weike Feng, Yuta Izumi, Amila Karunathilake

Ground based synthetic aperture radar (GB-SAR) is used to effectively mitigate natural disasters and monitor social infrastructure such as bridges, dams, and airport pavement surfaces. This book explains the fundamentals of radar technology, the principles of synthetic aperture radar (SAR) image generation, and interferometric SAR (InSAR) processing for observing small ground surface deformation less than 1 mm. More advanced multiple-input multiple-output (MIMO) radar for ground surface observation is introduced. The authors also provide examples of GB-SAR used for monitoring landslide and vegetation to show its potential and limitations. Understanding this advanced technology and its applications will help readers plan and install GB-SAR systems in real-life projects.

Features:

Introduces GB-SAR, an advanced tool that measures in-millimeter ground surface displacement. Explains how the GB-SAR system can be installed for landslide monitoring. Provides a new radar technology that monitors vibrations of infrastructure remotely. Discusses the advanced radar technology related to polarimetry and interferometry. Includes several case studies applying the tools and techniques discussed to natural disasters, such as landslides, volcanoes, glaciers, and so on.

This book is intended for civil professionals who deal with disaster mitigation and infrastructure monitoring and those in electrical engineering, including radar technology. It is also an excellent resource for upper-level undergraduate and graduate students taking courses in remote sensing and photogrammetry, geography, geodesy, information science, engineering, and geology, as well as researchers and scientists interested in learning the techniques and technologies for collecting, analyzing, managing, and visualizing geospatial data sets.

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