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Knowledge Discovery in Big Data from Astronomy and Earth Observation - 1st Edition - ISBN: 9780128191545, 9780128191552

Knowledge Discovery in Big Data from Astronomy and Earth Observation

1st Edition


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Editors: Petr Skoda Fathalrahman Adam
Paperback ISBN: 9780128191545
eBook ISBN: 9780128191552
Imprint: Elsevier
Published Date: 9th April 2020
Page Count: 472
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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.

Key Features

  • 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


Researchers and data scientists with focus on Geoscience, Remote sensing, and Astronomy. Computer scientists involved in astronomical and geoscience projects. Graduate students in astronomy and geoscience fields who are interested in a high level coverage of big data handling in these two fields

Table of Contents

1. Methodologies for Knowledge Discovery Processes in Context of AstroGeoInformatics

2. Historical Background of Big Data in Astro and Geo Context

3. AstroGeoInformatics: from Data Acquisition to Further Application

4. Synergy between astronomy and geosciences

5. Surveys, Catalogues, Databases and Archives of Astronomical data

6. Surveys, Catalogues, Databases/Archives and State-of-The-Art Methods for Geospatial data processing

7. International Database of Neutron Monitor Measurements: Development and Applications

8. High Performance Techniques for Big Data Processing

9. Query Processing and Access Methods for Big Astro and Geo Databases

10. Real Time Stream Processing in Astronomy

11. Time Series

12. Time Series Analysis of Generally Irregularly Spaced Signals

13. When Evolutionary Computing Meets Astro- and Geo- Informatics

14. Learning in Big Data: Introduction to Machine Learning

15. Deep Learning- An Opportunity and a Challenge for Geo- and Astrophysics

16. Astro Geo Informatics - Visually Guided Classification of Time Series Data

17. Multiwavelength Astronomy: Examples of Data-Mining

18. Applications of Big Data in Astronomy and Geosciences: Algorithms for Photographic Images, Processing and Error Elimination

19. Big Astronomical Data Sets and Discovery of New Celestial Bodies in the Solar System in Automated Mode by the CoLiTec Software

20. Big Data for the Magnetic Field Variations in Solar-Terrestrial Physics and their Wavelet Analysis

21. Monitoring the Earth Ionosphere by Listening to GPS Satellites

22. Exploitation of Big Real-time GNSS Databases for Weather Prediction

23. Application of Big Databases of Radio Observation in Investigation of Ionosphere, Natural Disaster Prediction and Telecommunication

24. Influence on Life Applications of a Federated Astro-Geo Data Base


No. of pages:
© Elsevier 2020
9th April 2020
Paperback ISBN:
eBook ISBN:

About the Editors

Petr Skoda

Petr Škoda has been involved in astroinformatics and has a long-term experience in using and lecturing the astronomical Virtual observatory. One of the proposers of COST BigSkyEarth Action and its MC member. BigSkyEarth is the working group behind the idea of the book and a conference about the same topic.

Affiliations and Expertise

Stellar Department, Astronomical Institute CAS, Czech Republic

Fathalrahman Adam

Fathalrahman Adam has good understanding of classical machine learning and new concepts, along with hands-on experience and published papers. He is involved in large scale applications using satellite data for earth observation, mainly multi-spectral data. He is a member of BigSkyEarth COST Action.

Affiliations and Expertise

Deutsches Zentrum für Luft- und Raumfahrt (DLR) German Aerospace Center Earth Observation Center, German Remote Sensing Data Center, Land Surface Oberpfaffenhofen, Germany

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