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Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing PDF Author: Ni-Bin Chang
Publisher: CRC Press
ISBN: 1351650637
Category : Technology & Engineering
Languages : en
Pages : 627

Book Description
In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing PDF Author: Ni-Bin Chang
Publisher: CRC Press
ISBN: 1498774342
Category : Technology & Engineering
Languages : en
Pages : 508

Book Description
In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing PDF Author: Ni-Bin Chang
Publisher: CRC Press
ISBN: 1351650637
Category : Technology & Engineering
Languages : en
Pages : 627

Book Description
In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Multisensor Data Fusion

Multisensor Data Fusion PDF Author: David Hall
Publisher: CRC Press
ISBN: 1420038540
Category : Technology & Engineering
Languages : en
Pages : 564

Book Description
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Optical Remote Sensing of Ocean Hydrodynamics

Optical Remote Sensing of Ocean Hydrodynamics PDF Author: Victor Raizer
Publisher: CRC Press
ISBN: 1351119176
Category : Technology & Engineering
Languages : en
Pages : 313

Book Description
Optical Remote Sensing is one of the main technologies used in sea surface monitoring. Optical Remote Sensing of Ocean Hydrodynamics investigates and demonstrates capabilities of optical remote sensing technology for enhanced observations and detection of ocean environments. It provides extensive knowledge of physical principles and capabilities of optical observations of the oceans at high spatial resolution, 1-4m, and on the observations of surface wave hydrodynamic processes. It also describes the implementation of spectral-statistical and fusion algorithms for analyses of multispectral optical databases and establishes physics-based criteria for detection of complex wave phenomena and hydrodynamic disturbances including assessment and management of optical databases. This book explains the physical principles of high-resolution optical imagery of the ocean surface, discusses for the first time the capabilities of observing hydrodynamic processes and events, and emphasizes the integration of optical measurements and enhanced data analysis. It also covers both the assessment and the interpretation of dynamic multispectral optical databases and includes applications for advanced studies and nonacoustic detection. This book is an invaluable resource for researches, industry professionals, engineers, and students working on cross-disciplinary problems in ocean hydrodynamics, optical remote sensing of the ocean and sea surface remote sensing. Readers in the fields of geosciences and remote sensing, applied physics, oceanography, satellite observation technology, and optical engineering will learn the theory and practice of optical interactions with the ocean.

Intelligent Data Mining and Fusion Systems in Agriculture

Intelligent Data Mining and Fusion Systems in Agriculture PDF Author: Xanthoula-Eirini Pantazi
Publisher: Academic Press
ISBN: 0128143924
Category : Business & Economics
Languages : en
Pages : 334

Book Description
Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. - Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture - Addresses AI use in weed management, disease detection, yield prediction and crop production - Utilizes case studies to provide real-world insights and direction

Remote Sensing of Climate

Remote Sensing of Climate PDF Author: Timothy Dube
Publisher: Elsevier
ISBN: 0443217300
Category : Technology & Engineering
Languages : en
Pages : 458

Book Description
Remote Sensing of Climate provides cutting-edge techniques in remote sensing of climate variability and the environment. The book focuses on methods and data analytics, advancements in scientific research in the field, and further proffers recommendations on the possible knowledge gaps and future scientific research directions. It covers eight key themes of remote sensing and climate variability, including discussions on how the various aspects from each chapter of the themes interrelate. It also integrates several divergent perspectives on remote sensing and climate variability and the environment to show the interrelationships between the perspectives. This is an important reference for those in education and research working on remote sensing and climate science who need methods, data analytics, case studies, research strides, and key knowledge gaps in the field. - Discusses advancements and future research directions in remote sensing for climate variability in a variety of environments - Includes simplified and condensed methodologies and data analytics - Provides case studies on remote sensing of climate variability, both of the Northern hemisphere temperate systems which are little affected by climate variability, and the greater-impacted global south

Agricultural Internet of Things and Decision Support for Precision Smart Farming

Agricultural Internet of Things and Decision Support for Precision Smart Farming PDF Author: Annamaria Castrignano
Publisher: Academic Press
ISBN: 0128183748
Category : Business & Economics
Languages : en
Pages : 472

Book Description
Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies. - Presents the science behind smart technologies for agricultural management - Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space - Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable

Remote Sensing in Applied Geophysics

Remote Sensing in Applied Geophysics PDF Author: Chiara Colombero
Publisher: MDPI
ISBN: 303943733X
Category : Science
Languages : en
Pages : 318

Book Description
The Special Issue is focused on recent and upcoming advances in the combined application of remote sensing and applied geophysics. Applied geophysics analyzes the distribution of physical properties in the subsurface for a wide range of geological, engineering, and environmental applications at different scales. Seismic, electrical, magnetic, and electromagnetic methods are among the most applied and well-established geophysical techniques. These methods share the advantages of being non-invasive and exploring wide areas of investigation with respect to conventional methods (e.g., drilling). Geophysical surveys are usually carried out deploying or moving the appropriate instrumentation directly on the ground surface. However, recent technological advances have resulting in the development of innovative acquisition systems becoming more typical of the remote sensing community (e.g., airborne surveys). While applied geophysics mainly focuses on the subsurface, typical remote sensing techniques have the ability to accurately image the Earth’s surface with high-resolution investigations carried out by means of terrestrial, airborne, or satellite-based platforms. The integration of surface and subsurface information is often crucial for several purposes, including the processing of geophysical data, the characterization and time-lapse monitoring of surface and near-surface targets, and the reconstruction of highly detailed and comprehensive 3D models of the investigated areas. Recent contributions showing the added value of surface reconstruction and/or monitoring in the processing, interpretation, and cross-comparison of geophysical techniques for archaeological, environmental, and engineering studies are collected in this book. Pioneering geophysical acquisitions by means of innovative remote systems are also presented.

Multi-Sensor Information Fusion

Multi-Sensor Information Fusion PDF Author: Xue-Bo Jin
Publisher: MDPI
ISBN: 3039283022
Category : Technology & Engineering
Languages : en
Pages : 602

Book Description
This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Advances in Passive Microwave Remote Sensing of Oceans

Advances in Passive Microwave Remote Sensing of Oceans PDF Author: Victor Raizer
Publisher: CRC Press
ISBN: 1040095844
Category : Technology & Engineering
Languages : en
Pages : 342

Book Description
This new edition introduces the fundamentals of passive microwave remote sensing of oceans, including the physical principles of microwave radiometry, novel observational data, their interpretation, and applications. It not only demonstrates and examines the recent advantages and state of the art of microwave data but also provides guidance for explaining complex ocean studies and advanced applications. All chapters are thoroughly updated with detailed analysis of space‐based microwave missions, and a new chapter on space‐based microwave radiometer experiments has been added. This book discusses the power of microwave remote sensing as an efficient tool for diagnostics of ocean phenomena in research and education. Features New to this Edition: • Includes a new chapter and additional data, images, illustrations, and references. • Uses ocean microwave data, acquired from different platforms, to illustrate different methods of analysis and interpretation. • Updates information on recent and important satellite missions dedicated to microwave remote sensing of oceans. • Offers more detailed analysis of multiband microwave data and images. • Provides examples of microwave data that cover different ocean environmental phenomena and hydro‐physical fields, including global and local ocean features. • Presents additional material on advanced applications, including detection capabilities. This book is intended for postgraduate students and professionals working in fields related to remote sensing, geography, oceanography, civil, environmental, and geotechnical engineering.