Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Book

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

  • Author : Ni-Bin Chang
  • Publisher : CRC Press
  • Release Date : 2018-02-21
  • Genre: Technology & Engineering
  • Pages : 508
  • ISBN 10 : 9781498774345

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Excerpt :

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

Optical Remote Sensing of Ocean Hydrodynamics Book

Optical Remote Sensing of Ocean Hydrodynamics

  • Author : Victor Raizer
  • Publisher : CRC Press
  • Release Date : 2019-03-04
  • Genre: Technology & Engineering
  • Pages : 280
  • ISBN 10 : 9781351119177

Optical Remote Sensing of Ocean Hydrodynamics Excerpt :

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.

Multisensor Data Fusion Book

Multisensor Data Fusion

  • Author : David Hall
  • Publisher : CRC Press
  • Release Date : 2001-06-20
  • Genre: Technology & Engineering
  • Pages : 568
  • ISBN 10 : 9781420038545

Multisensor Data Fusion Excerpt :

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

Machine Learning for Planetary Science Book

Machine Learning for Planetary Science

  • Author : Joern Helbert
  • Publisher : Elsevier
  • Release Date : 2022-03-25
  • Genre: Science
  • Pages : 232
  • ISBN 10 : 9780128187227

Machine Learning for Planetary Science Excerpt :

Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation. Includes links to a code repository for sharing codes and examples, some of which include executable Jupyter notebook files that can serve as tutorials Presents methods applicable to everyday problems faced by planetary scientists and sufficient for analyzing large datasets Serves as a guide for selecting the right method and tools for applying machine learning to particular analysis problems Utilizes case studies to illustrate how machine learning methods can be employed in practice

Remote Sensing in Applied Geophysics Book

Remote Sensing in Applied Geophysics

  • Author : Chiara Colombero
  • Publisher : MDPI
  • Release Date : 2020-12-07
  • Genre: Science
  • Pages : 318
  • ISBN 10 : 9783039437337

Remote Sensing in Applied Geophysics Excerpt :

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.

Pattern Recognition and Artificial Intelligence Book

Pattern Recognition and Artificial Intelligence

  • Author : Chawki Djeddi
  • Publisher : Springer Nature
  • Release Date : 2021-03-17
  • Genre: Computers
  • Pages : 341
  • ISBN 10 : 9783030718046

Pattern Recognition and Artificial Intelligence Excerpt :

This book constitutes the refereed proceedings of the 4th Mediterranean Conference on Pattern Recognition and Artificial Intelligence, MedPRAI 2020, held in Hammamet, Tunisia, in December 2020.​ Due to the COVID-19 pandemic the conference was held online. The 24 revised papers presented were thoroughly reviewed and selected from 72 submissions. The papers are covering the topics of recent advancements in different areas of pattern recognition and artificial intelligence, such as statistical, structural and syntactic pattern recognition, machine learning, data mining, neural networks, computer vision, multimedia systems, information retrieval, etc.

Multi Sensor Image Fusion and Its Applications Book

Multi Sensor Image Fusion and Its Applications

  • Author : Rick S. Blum
  • Publisher : CRC Press
  • Release Date : 2018-10-03
  • Genre: Technology & Engineering
  • Pages : 528
  • ISBN 10 : 9781420026986

Multi Sensor Image Fusion and Its Applications Excerpt :

Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies. After a review of state-of-the-art image fusion techniques, the book provides an overview of fusion algorithms and fusion performance evaluation. The following chapters explore recent progress and practical applications of the proposed techniques to solving problems in such areas as medical diagnosis, surveillance and biometric systems, remote sensing, nondestructive evaluation, blurred image restoration, and image quality assessment. Recognized leaders from industry and academia contribute the chapters, reflecting the latest research trends and providing useful algorithms to aid implementation. Supplying a 28-page full-color insert, Multi-Sensor Image Fusion and Its Applications clearly demonstrates the benefits and possibilities of this revolutionary development. It provides a solid knowledge base for applying these cutting-edge techniques to new challenges and creating future advances.

Deep Learning for Remote Sensing Images with Open Source Software Book

Deep Learning for Remote Sensing Images with Open Source Software

  • Author : Rémi Cresson
  • Publisher : CRC Press
  • Release Date : 2020-07-15
  • Genre: Technology & Engineering
  • Pages : 152
  • ISBN 10 : 9781000093612

Deep Learning for Remote Sensing Images with Open Source Software Excerpt :

In today’s world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source Software is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data. Specific Features of this Book: The first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow) Presents approaches suited for real world images and data targeting large scale processing and GIS applications Introduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration) Suited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills. Includes deep learning techniques through many step by step remote sensing data processing exercises.

Multi sensor System Applications in the Everglades Ecosystem Book

Multi sensor System Applications in the Everglades Ecosystem

  • Author : Caiyun Zhang
  • Publisher : CRC Press
  • Release Date : 2020-01-06
  • Genre: Science
  • Pages : 336
  • ISBN 10 : 9780429530784

Multi sensor System Applications in the Everglades Ecosystem Excerpt :

This book explores the applicability of multiple remote sensors to acquire information relevant to restoration and conservation efforts in wetlands using data collected from airborne and space multispectral/hyperspectral sensors, light detection and ranging (LiDAR), Unmanned Aircraft Systems (UAS), and a hand-held spectroradiometer. This book also examines digital data processing techniques such as object-based image analysis, machine learning, texture analysis, and data fusion. After an introduction to the Everglades and to remote sensing, the book is divided into four parts based on the sensor systems used. There are chapters on vegetation mapping, biomass and water quality modeling, applications of hyperspectral data for plant stress analysis and coral reef mapping, studies of airborne LiDAR data for coastal vulnerability analysis and DEM improvement, as well as chapters that explore a fusion of multiple sensors for different datasets. Features Introduces concepts, theories, and advanced processing techniques A complete introduction of machine learning, object-based image analysis, data fusion, and ensemble analysis techniques in processing data from multiple remote sensors Explains how multiple remote sensing systems are applied in the wetland ecosystems of Florida The author had been teaching and using both systems and her research is widely recognized Multi-sensor System Applications in the Everglades Ecosystems provides a comprehensive application of remote sensing techniques in the Florida Everglades and its coastal ecosystems. It will prove an invaluable resource for the restoration and conservation of the Florida Everglades and beyond, for global wetlands in general. Any professional, scientist, engineer, or student working with remote sensing and wetland ecosystems will reap enormous benefits from this book.

Environmental Remote Sensing in Flooding Areas Book

Environmental Remote Sensing in Flooding Areas

  • Author : Chunxiang Cao
  • Publisher : Springer Nature
  • Release Date : 2020-12-12
  • Genre: Technology & Engineering
  • Pages : 148
  • ISBN 10 : 9789811582028

Environmental Remote Sensing in Flooding Areas Excerpt :

This book introduces flood inundation area and flood risks assessment based on a comprehensive monitoring system using remote sensing and geographic information system technologies. Taking the 2011 flood disaster of Ayutthaya in Thailand as an example, it presents a flood intrusion zone identification method based on remote sensing technology, spatial information technology and geographic information system for flood disaster monitoring and early warning system. It introduces the study area and data, vegetation index, improved support vector machine and flood intrusion zone identification method. It also analyzes the flood remote sensing parameters and waterborne diseases, method of risk assessment of waterborne disease outbreak, waterborne disease outbreak risk monitoring based on backpropagation neural network and its expert system. It not only promotes a new interdisciplinary approach both in public health and space information technology, but also greatly supports decision makers in disaster reduction.

Remote Sensing of Environmental Changes in Cold Regions Book

Remote Sensing of Environmental Changes in Cold Regions

  • Author : Jinyang Du
  • Publisher : MDPI
  • Release Date : 2019-11-14
  • Genre: Technology & Engineering
  • Pages : 210
  • ISBN 10 : 9783039215706

Remote Sensing of Environmental Changes in Cold Regions Excerpt :

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing.

Grasslands and Climate Change Book

Grasslands and Climate Change

  • Author : David J. Gibson
  • Publisher : Cambridge University Press
  • Release Date : 2019-03-21
  • Genre: Nature
  • Pages : 372
  • ISBN 10 : 9781107195264

Grasslands and Climate Change Excerpt :

A comprehensive assessment of the effects of climate change on global grasslands and the mitigating role that ecologists can play.

Applications of Small Unmanned Aircraft Systems Book

Applications of Small Unmanned Aircraft Systems

  • Author : J.B. Sharma
  • Publisher : CRC Press
  • Release Date : 2019-10-18
  • Genre: Technology & Engineering
  • Pages : 290
  • ISBN 10 : 9780429534324

Applications of Small Unmanned Aircraft Systems Excerpt :

Advances in high spatial resolution mapping capabilities and the new rules established by the Federal Aviation Administration in the United States for the operation of Small Unmanned Aircraft Systems (sUAS) have provided new opportunities to acquire aerial data at a lower cost and more safely versus other methods. A similar opening of the skies for sUAS applications is being allowed in countries across the world. Also, sUAS can access hazardous or inaccessible areas during disaster events and provide rapid response when needed. Applications of Small Unmanned Aircraft systems: Best Practices and Case Studies is the first book that brings together the best practices of sUAS applied to a broad range of issues in high spatial resolution mapping projects. Very few sUAS pilots have the knowledge of how the collected imagery is processed into value added mapping products that have commercial and/or academic import. Since the field of sUAS applications is just a few years old, this book covers the need for a compendium of case studies to guide the planning, data collection, and most importantly data processing and map error issues, with the range of sensors available to the user community. Written by experienced academics and professionals, this book serves as a guide on how to formulate sUAS based projects, from choice of a sUAS, flight planning for a particular application, sensors and data acquisition, data processing software, mapping software and use of the high spatial resolution maps produced for particular types of geospatial modeling. Features: Focus on sUAS based data acquisition and processing into map products Broad range of case studies by highly experienced academics Practical guidance on sUAS hardware, sensors, and software utilized Compilation of workflow insights from expert professors and professionals Relevant to academia, government, and industry Positional and thematic map accuracy, UAS curriculum development and workflow replicability issues This book

Information Technology in Geo Engineering Book

Information Technology in Geo Engineering

  • Author : António Gomes Correia
  • Publisher : Springer Nature
  • Release Date : 2019-09-24
  • Genre: Science
  • Pages : 924
  • ISBN 10 : 9783030320294

Information Technology in Geo Engineering Excerpt :

These proceedings address the latest developments in information communication and technologies for geo-engineering. The 3rd International Conference on Information Technology in Geo-Engineering (ICITG 2019), held in Guimarães, Portugal, follows the previous successful installments of this conference series in Durham (2014) and Shanghai (2010). The respective chapters cover the following: Use of information and communications technologies Big data and databases Data mining and data science Imaging technologies Building information modelling applied to geo-structures Artificial intelligence Smart geomaterials and intelligent construction Sensors and monitoring Asset management Case studies on design, construction and maintenance Given its broad range of coverage, the book will benefit students, educators, researchers and professional practitioners alike, encouraging these readers to help take the geo-engineering community into the digital age

Deep Learning for the Earth Sciences Book

Deep Learning for the Earth Sciences

  • Author : Gustau Camps-Valls
  • Publisher : John Wiley & Sons
  • Release Date : 2021-08-18
  • Genre: Technology & Engineering
  • Pages : 432
  • ISBN 10 : 9781119646167

Deep Learning for the Earth Sciences Excerpt :

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.