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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.
Synthetic Aperture Radar Imaging Mechanism for Oil Spills delivers the critical tool needed to understand the latest technology in radar imaging of oil spills, particularly microwave radar as a main source to understand analysis and applications in the field of marine pollution. Filling the gap between modern physics quantum theory and applications of radar imaging of oil spills, this reference is packed with technical details associated with the potentiality of synthetic aperture radar (SAR) and the key methods used to extract the value-added information necessary, such as location, size, perimeter and chemical details of the oil slick from SAR measurements. Rounding out with practical simulation trajectory movements of oil spills using radar images, this book brings an effective new source of technology and applications for today's oil and marine pollution engineers. - Bridges the gap between theory and application of the techniques involving oil spill monitoring - Helps readers understand a new approach to four-dimensional automatic detection - Provides advanced knowledge on image processing based on intelligent learning machine algorithms and new techniques for detection, such as quantum and multi-objective algorithms
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.
Provides a scientific basis for the cleanup and for the assessment of oil spills Enables Non-scientific officers to understand the science they use on a daily basis Multi-disciplinary approach covering fields as diverse as biology, microbiology, chemistry, physics, oceanography and toxicology Covers the science of oil spills from risk analysis to cleanup and through the effects on the environment Includes case studies examining and analyzing spills, such as Tasman Spirit oil spill on the Karachi Coast, and provides lessons to prevent these in the future
The classic reference for radar and remote sensing engineers, Handbook of Radar for Scattering Statistics for Terrain, has been reissued with updated, practical software for modern data analysis applications. First published in 1989, this update features a new preface, along with three new appendices that explain how to use the new software and graphical user interface. Python- and MATLAB-based software has been utilized so remote sensing and radar engineers can utilize the wealth of statistical data that came with the original book and software. This update combines the book and software, previously sold separately, into a single new product. The text first presents detailed examinations of the statistical behavior of speckle when superimposed on nonuniform terrain. The Handbook of Radar Scattering Statistics for Terrain then supports system design and signal processing applications with a complete database of calibrated backscattering coefficients. Compiled over 30 years, the statistical summaries of radar backscatter from terrain offers you over 400,000 data points compiled in tabular format. With this text, you'll own the most comprehensive database of radar terrain scattering statistics ever compiled. Derived from measurements made by both airborne and ground-based scatterometer systems, the database includes information from 114 references. The text provides over 60 tables of backscatter data for 9 different surface categories, all derived under strict quality criteria. Rigorous standards for calibration accuracy, measurement precision, and category identification make the database the most reliable source for scattering statistics ever available.
Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations.
Advanced Algorithms for Mineral and Hydrocarbon Exploration Using Synthetic Aperture Radar is a research- and practically-based reference that bridges the gap between the remote sensing industry and the mineral and hydrocarbon exploration industry. In this context, the book explains how to commercialize the applications of synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for mineral and hydrocarbon exploration. This multidisciplinary reference is useful for oil and gas companies, the mining industry, geoscientists, and coastal and petroleum engineers. Presents both theoretical and practical applications of various types of remote sensing for hydrocarbon and mineral exploration Covers specific problems for exploration professionals and provides applications for solving each problem Includes more than 100 images and figures to help explain the concepts and applications described in the book
Advanced Algorithms for Mineral and Hydrocarbon Exploration Using Synthetic Aperture Radar is a research- and practically-based reference that bridges the gap between the remote sensing industry and the mineral and hydrocarbon exploration industry. In this context, the book explains how to commercialize the applications of synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for mineral and hydrocarbon exploration. This multidisciplinary reference is useful for oil and gas companies, the mining industry, geoscientists, and coastal and petroleum engineers. - Presents both theoretical and practical applications of various types of remote sensing for hydrocarbon and mineral exploration - Covers specific problems for exploration professionals and provides applications for solving each problem - Includes more than 100 images and figures to help explain the concepts and applications described in the book
Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany’s mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA). Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today’s minerology and petroleum engineers. Key Features • Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. • Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. • Includes over 200 equations that illustrate how to follow examples in the book.
Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modelling is both a research- and practice-based reference that bridges the gap between the remote sensing field and the dynamic oceanography exploration field. In this perspective, the book explicates how to apply techniques in synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for oceanic turbulence and front simulation and modelling. The book includes detailed algorithms to enable readers to better understand and implement the practices covered in their own work and apply QInSAR to their own research.This multidisciplinary reference is useful for researchers and academics in dynamic oceanography and modelling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers - Details the potential of synthetic aperture radar in imaging ocean surface dynamical features - Includes detailed algorithms and methods, allowing readers to develop their own computer algorithms - Covers the latest applications of quantum image processing