Advances in GNSS Reflectometry
Receiver Design, Signal Processing, Machine Learning-Based Model Construction, and Disaster Monitoring
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Beschreibung
This book is dedicated to advances in the theory and practice of GNSS reflectometry. It covers a variety of topics in this emerging remote sensing technology, including retrieval of soil moisture, snow depth and snow water equivalent, underground coal mining induced ground subsidence, sea surface height, wind speed and direction, sea surface wave height and rainfall intensity; detection of sea ice, ships, land water body, sea surface rainfall; and data calibration and design of antenna and receiver. It also briefly presents the theory and application of GNSS SAR imaging. The book makes use of ground-based, airborne, and spaceborne data for land and ocean applications especially those related to disasters such as droughts, floods, hurricanes, typhoons, and damaging sea waves. Extensive data processing and experimental results are presented in the major chapters.
This book is dedicated to advances in the theory and practice of GNSS reflectometry. It covers a variety of topics in this emerging remote sensing technology, including retrieval of soil moisture, snow depth and snow water equivalent, underground coal mining induced ground subsidence, sea surface height, wind speed and direction, sea surface wave height and rainfall intensity; detection of sea ice, ships, land water body, sea surface rainfall; and data calibration and design of antenna and receiver. It also briefly presents the theory and application of GNSS SAR imaging. The book makes use of ground-based, airborne, and spaceborne data for land and ocean applications especially those related to disasters such as droughts, floods, hurricanes, typhoons, and damaging sea waves. Extensive data processing and experimental results are presented in the major chapters.
Presents current advances in theory and practice of GNSS reflectometry Provides comprehensive treatment of detection and warning of land and ocean disasters Presents a variety of machine learning-based methods in the construction of retrieval models
Autor*in
Kegen Yu
Themen in »Advances in GNSS Reflectometry«
GNSS reflectometry GNSS SAR imaging ocean and land application disaster monitoring spaceborne data airborne data ground-based data