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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 Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences
The advance in space machineries has created a novel technology for observing and monitoring the Earth from space. Most earth observation remote sensing considerations focus on using conventional image processing algorithms or classic edge detection tools. Nevertheless, these techniques do not implement modern physics, applied mathematics, signal communication, remote sensing data, and innovative space technologies. This book provides readers with methods to comprehend how to monitor coastal environments, disaster areas, and infrastructure from space with advanced talent remote sensing technology to bridge the gaps between modern space technology, image processing algorithms, mathematical models and the critical issue of the coastal and infrastructure investigations.
The innovation in space technologies has generated a new method for observing and monitoring tsunamis from space. Most tsunami remote sensing studies focus on using classical image processing tools or conventional edge detection procedures. However, these methods do not use modern physics, applied mathematics, signal communication, remote sensing data and innovative space technologies. This book equips readers to understand how to monitor tsunamis from space with remote sensing technology art to create a better alarm warning system.
Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. Comprehensive overview of various practical methods and algorithms Detailed description of the principles and procedures of the state-of-the-art algorithms Real-world case studies open several chapters More than 500 full-color figures and tables Edited by top remote sensing experts with contributions from authors across the geosciences
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.
This book introduces the use of various remote sensing data such as microwave, hyperspectral and very high-resolution (VHR) satellite imagery; mapping techniques including pixel and object-based machine learning; and geostatistical modelling techniques including cellular automation, entropy and land fragmentation. Remote sensing plays a vital role in solving urban and environmental challenges at the landscape level. Globally, more than half of the urban population is facing severe environmental and social challenges, especially those relating to climate change, agricultural land encroachment, green infrastructure and environmental degradation, mobility due to rapid rural–urban transformation and anthropogenic interventions. Mapping and quantification of such threats at the landscape level are challenging for experts using traditional techniques; however, remote sensing technology provides diverse spatial data at a varying scale, volume and accessibility for mapping and modelling, and it also analyses challenges at urban and landscape levels. Together, they address challenges at urban and landscape levels to support the Sustainable Development Goals (SDGs).
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
Sea Ice: Physics and Remote Sensing addresses experiences acquired mainly in Canada by researchers in the fields of ice physics and growth history in relation to its polycrystalline structure as well as ice parameters retrieval from remote sensing observations. The volume describes processes operating at the macro- and microscale (e.g., brine entrapment in sea ice, crystallographic texture of ice types, brine drainage mechanisms, etc.). The information is supported by high-quality photographs of ice thin-sections prepared from cores of different ice types, all obtained by leading experts during field experiments in the 1970s through the 1990s, using photographic cameras and scanning microscopy. In addition, this volume presents techniques to retrieve a suite of sea ice parameters (e.g. ice type, concentration, extent, thickness, surface temperature, surface deformation, etc.) from space-borne and airborne sensor data. The breadth of the material on this subject is designed to appeal to researchers and users of remote sensing data who want to develop quick familiarity with the capabilities of this technology or detailed knowledge about major techniques for retrieval of key ice parameters. Volume highlights include: Detailed crystallographic classification of natural sea ice, the key information from which information about ice growth conditions can be inferred. Many examples are presented with material to support qualitative and quantitative interpretation of the data. Methods developed for revealing microstructural characteristics of sea ice and performing forensic investigations. Data sets on radiative properties and satellite observations of sea ice, its snow cover, and surrounding open water. Methods of retrieval of ice surface features and geophysical parameters from remote sensing observations with a focus on critical issues such as the suitability of different sensors for different tasks and data synergism. Sea Ice: Physics and Remote Sensing is intended for a variety of sea ice audiences interested in different aspects of ice related to physics, geophysics, remote sensing, operational monitoring, mechanics, and cryospheric sciences.
This book provides insights into the benefits of using remote sensing data from a geoscientist's perspective, by integrating the data with the understanding of Earth's surface and subsurface. In 3 sections, the book takes a detailed look at what data explorationists use when they explore for hydrocarbon resources, assess different terrain types for planning and hazards and extract present-day geologic analogs for subsurface geologic settings. The book presents the usage of remote sensing data in exploration in a structured way by detecting individual geologic features as building blocks for complex geologic systems. This concept enables readers to build their own workflows for the assessment of complex geologic systems using various combinations of remote sensing data. Section 1 introduces readers to the foundations of remote sensing for exploration, covers various methods of image processing and studies different digital elevation and bathymetry models. Section 2 presents the concept of geomorphology as a means to integrate surface and subsurface data. Different aspects of rendering in 2D and 3D are explained and used for the interpretation and extraction of geologic features that are used in exploration. Section 3 addresses remote sensing for hydrocarbon exploration in detail, from geophysical data acquisition to development and infrastructure planning. The organization of this chapter follows an exploration workflow from regional to local modeling studying basin and petroleum system modeling as well as logistics planning of seismic surveys and near-surface modeling. Aspects of field development and infrastructure planning comprise multi-temporal and dynamic modeling. The section closes with a structured approach to extracting geologic analogs from interpreted remote sensing data. The book will be of interest to professionals and students working in exploration for hydrocarbons and water resources, as well as geoscientists and engineers using remote sensing for infrastructure planning, hazard assessment and dynamic environmental studies.