Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
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
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
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:
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.
Stellar Department, Astronomical Institute CAS, Czech Republic
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.
Deutsches Zentrum für Luft- und Raumfahrt (DLR) German Aerospace Center Earth Observation Center, German Remote Sensing Data Center, Land Surface Oberpfaffenhofen, Germany
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.