This report provides a detailed evaluation of synthetic aperture radar (SAR) as a potential technology improvement over the Coast Guard's existing side-looking airborne radar (SLAR) for oil-spill surveillance applications. The U.S. Coast Guard Research and Development Center (R & D Center), Environmental Safety Branch, sponsored a joint experiment including the U.S. Coast Guard, Sandia National Laboratories, and the National Oceanographic and Atmospheric Administration (NOAA), Hazardous Materials Division. Radar imaging missions were flown on six days over the coastal waters off Santa Barbara, CA, where there are constant natural seeps of oil. Both the Coast Guard SLAR and the Sandia National Laboratories SAR were employed to acquire simultaneous images of oil slicks and other natural sea surface features that impact oil-spill interpretation. Surface truth and other environmental data were also recorded during the experiment. The experiment data were processed at Sandia National Laboratories and delivered to the R & D Center on a PC-based computer workstation for analysis by experiment participants.

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

U.S. Arctic waters north of the Bering Strait and west of the Canadian border encompass a vast area that is usually ice covered for much of the year, but is increasingly experiencing longer periods and larger areas of open water due to climate change. Sparsely inhabited with a wide variety of ecosystems found nowhere else, this region is vulnerable to damage from human activities. As oil and gas, shipping, and tourism activities increase, the possibilities of an oil spill also increase. How can we best prepare to respond to such an event in this challenging environment? Responding to Oil Spills in the U.S. Arctic Marine Environment reviews the current state of the science regarding oil spill response and environmental assessment in the Arctic region north of the Bering Strait, with emphasis on the potential impacts in U.S. waters. This report describes the unique ecosystems and environment of the Arctic and makes recommendations to provide an effective response effort in these challenging conditions. According to Responding to Oil Spills in the U.S. Arctic Marine Environment, a full range of proven oil spill response technologies is needed in order to minimize the impacts on people and sensitive ecosystems. This report identifies key oil spill research priorities, critical data and monitoring needs, mitigation strategies, and important operational and logistical issues. The Arctic acts as an integrating, regulating, and mediating component of the physical, atmospheric and cryospheric systems that govern life on Earth. Not only does the Arctic serve as regulator of many of the Earth's large-scale systems and processes, but it is also an area where choices made have substantial impact on life and choices everywhere on planet Earth. This report's recommendations will assist environmentalists, industry, state and local policymakers, and anyone interested in the future of this special region to preserve and protect it from damaging oil spills.

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

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.