Synthetic Aperture Radar Automatic Detection Algorithms (SARADA) for Oil Spills conveys the pivotal tool required to fully comprehend the advanced algorithms in radar monitoring and detection of oil spills, particularly quantum computing and algorithms as a keystone to comprehending theories and algorithms behind radar imaging and detection of marine pollution. Bridging the gap between modern quantum mechanics and computing detection algorithms of oil spills, this book contains precise theories and techniques for automatic identification of oil spills from SAR measurements. Based on modern quantum physics, the book also includes the novel theory on radar imaging mechanism of oil spills.
With the use of precise quantum simulation of trajectory movements of oil spills using a sequence of radar images, this book demonstrates the use of SARADA for contamination by oil spills as a promising novel technique.
Key Features:
Introduces basic concepts of a radar remote sensing.
Fills a gap in the knowledge base of quantum theory and microwave remote sensing.
Discusses the important aspects of oil spill imaging in radar data in relation to the quantum theory.
Provides recent developments and progresses of automatic detection algorithms of oil spill from radar data.
Presents 2-D oil spill radar data in 4-D images.
Microwave Remote Sensing based on Maxwell Equations. Quantization of
Maxwells Equation and Electromagnetic Field. Quantum Signals at Microwave
Devices. Quantum Mechanical of Scattering Cross-Section Theory. Quantization
of Radar Theory. Theories of Synthetic Aperture Radar. Novel Relativity
Theories of Synthetic Aperture Radar. Quantization of Oil Spill Imagining in
Synthetic Aperture Radar. Texture and Quantum Entropy Algorithms for Oil
Spill Detection in Synthetic Aperture Radar Images. Mahalanobis Classifier
and Neural Network Algorithms for Oil Spill Detection. Fractal Algorithm for
Discrimination between Oil Spill and Look-Alike. Quantum Cellular Automata
Algorithm for Automatic Detection of Oil Spills and Look-Alikes. Simulation
of Trajectory Movements of Oil Spill in Multisar Satellite Data Using Quantum
Hopfield Algorithm.
Maged Marghany is currently a professor of remote sensing in the Faculty of Geospatial and Real Estate, Geomatika University College (GUC), Malaysia. He authored Advanced Remote Sensing Technology for Tsunami Modelling and Forecasting, published in 2018. His research focuses on microwave remote sensing and remote sensing for mineralogy detection and mapping. Previously, he worked as a Deputy Director in Research and Development at the Institute of Geospatial Science and Technology and the Department of Remote Sensing, both at Universiti Teknologi Malaysia. Maged has earned many degrees, including a post-doctoral in radar remote sensing from the International Institute for Aerospace Survey and Earth Sciences, a PhD in environmental remote sensing from the Universiti Putra Malaysia, a Master of Science in physical oceanography from the University Pertanian Malaysia, general and special diploma of Education and a Bachelor of Science in physical oceanography from the University of Alexandria in Egypt. Maged has published well over 250 papers in international conferences and journals and is active in International Geoinformatics, and the International Society for Photogrammetry and Remote Sensing (ISPRS).
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