Knowledge Discovery in Big Data from Astronomy and Earth Observation Book

Knowledge Discovery in Big Data from Astronomy and Earth Observation


  • Author : Petr Skoda
  • Publisher : Elsevier
  • Release Date : 2020-04-23
  • Genre: Science
  • Pages : 472
  • ISBN 10 : 9780128191545
  • Total Read : 82
  • File Size : 11,9 Mb

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Knowledge Discovery in Big Data from Astronomy and Earth Observation Summary:

Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. Addresses both astronomy and geosciences in parallel, from a big data perspective Includes introductory information, key principles, applications and the latest techniques Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields

Knowledge Discovery in Big Data from Astronomy and Earth Observation Book

Knowledge Discovery in Big Data from Astronomy and Earth Observation


  • Author : Petr Skoda
  • Publisher : Elsevier
  • Release Date : 2020-04-10
  • Genre: Science
  • Pages : 472
  • ISBN 10 : 9780128191552
  • Total Read : 59
  • File Size : 10,6 Mb

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Knowledge Discovery in Big Data from Astronomy and Earth Observation Summary:

Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants. Addresses both astronomy and geosciences in parallel, from a big data perspective Includes introductory information, key principles, applications and the latest techniques Well-supported by computing and information science-oriented chapters to introduce the necessary knowledge in these fields

Big Data in Astronomy Book

Big Data in Astronomy


  • Author : Linghe Kong
  • Publisher : Elsevier
  • Release Date : 2020-06-13
  • Genre: Science
  • Pages : 438
  • ISBN 10 : 9780128190852
  • Total Read : 60
  • File Size : 11,6 Mb

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Big Data in Astronomy Summary:

Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy. Bridges the gap between radio astronomy and computer science Includes coverage of the observation lifecycle as well as data collection, processing and analysis Presents state-of-the-art research and techniques in big data related to radio astronomy Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)

Earth Observation Data Cubes Book

Earth Observation Data Cubes


  • Author : Gregory Giuliani
  • Publisher : MDPI
  • Release Date : 2020-03-16
  • Genre: Science
  • Pages : 302
  • ISBN 10 : 9783039280926
  • Total Read : 66
  • File Size : 15,7 Mb

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Earth Observation Data Cubes Summary:

Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10× in the last 5 years); velocity (e.g., Sentinel-2 is capturing a new image of any given place every 5 days); and variety (e.g., different types of sensors, spatial/spectral resolutions). Traditional approaches to the acquisition, management, distribution, and analysis of EO data have limitations (e.g., data size, heterogeneity, and complexity) that impede their true information potential to be realized. Addressing these big data challenges requires a change of paradigm and a move away from local processing and data distribution methods to lower the barriers caused by data size and related complications in data management. To tackle these issues, EO data cubes (EODC) are a new paradigm revolutionizing the way users can store, organize, manage, and analyze EO data. This Special Issue is consequently aiming to cover the most recent advances in EODC developments and implementations to broaden the use of EO data to larger communities of users, support decision-makers with timely and actionable information converted into meaningful geophysical variables, and ultimately unlock the information power of EO data.

Earth Observation Open Science and Innovation Book

Earth Observation Open Science and Innovation


  • Author : Pierre-Philippe Mathieu
  • Publisher : Springer
  • Release Date : 2018-01-23
  • Genre: Science
  • Pages : 330
  • ISBN 10 : 9783319656335
  • Total Read : 84
  • File Size : 17,9 Mb

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Earth Observation Open Science and Innovation Summary:

This book is published open access under a CC BY 4.0 license. Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites. This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.

Planets  Stars and Stellar Systems Book

Planets Stars and Stellar Systems


  • Author : Howard E. Bond
  • Publisher : Springer
  • Release Date : 2013-02-27
  • Genre: Science
  • Pages : 508
  • ISBN 10 : 9400756178
  • Total Read : 86
  • File Size : 16,6 Mb

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Planets Stars and Stellar Systems Summary:

This is volume 2 of Planets, Stars and Stellar Systems, a six-volume compendium of modern astronomical research, covering subjects of key interest to the main fields of contemporary astronomy. This volume on “Astronomical Techniques, Software, and Data” edited by Howard E. Bond presents accessible review chapters on Astronomical Photometry, Astronomical Spectroscopy, Infrared Astronomy Fundamentals, Astronomical Polarimetry: Polarized Views of Stars and Planets, Sky Surveys,Techniques of Radio Astronomy,Radio and Optical Interferometry: Basic Observing Techniques and Data Analysis, Absolute Calibration of Spectrophotometric Standard Stars,Virtual Observatories, Data Mining, and Astroinformatics, Statistical Methods for Astronomy, Numerical Techniques in Astrophysics . All chapters of the handbook were written by practicing professionals. They include sufficient background material and references to the current literature to allow readers to learn enough about a specialty within astronomy, astrophysics and cosmology to get started on their own practical research projects. In the spirit of the series Stars and Stellar Systems published by Chicago University Press in the 1960s and 1970s, each chapter of Planets, Stars and Stellar Systems can stand on its own as a fundamental review of its respective sub-discipline, and each volume can be used as a textbook or recommended reference work for advanced undergraduate or postgraduate courses. Advanced students and professional astronomers in their roles as both lecturers and researchers will welcome Planets, Stars and Stellar Systems as a comprehensive and pedagogical reference work on astronomy, astrophysics and cosmology.

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 : 647
  • ISBN 10 : 9781351650632
  • Total Read : 91
  • File Size : 15,6 Mb

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

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

Data and Society Book

Data and Society


  • Author : Anne Beaulieu
  • Publisher : SAGE
  • Release Date : 2021-10-27
  • Genre: Social Science
  • Pages : 272
  • ISBN 10 : 9781529765120
  • Total Read : 93
  • File Size : 18,9 Mb

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Data and Society Summary:

Data and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.