Big Data Analytics in Earth, Atmospheric, and Ocean Sciences
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Big Data Analytics in Earth, Atmospheric, and Ocean Sciences

Big Data Analytics in Earth, Atmospheric, and Ocean Sciences

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About the Book

Applying tools for data analysis to the rapidly increasing volume of data about the Earth An ever-increasing volume of Earth data is being gathered. These data are “big” not only in size but also in their complexity, different formats, and varied scientific disciplines. As such, big data are disrupting traditional research. New methods and platforms, such as the cloud, are tackling these new challenges. Big Data Analytics in Earth, Atmospheric, and Ocean Sciences explores new tools for the analysis and display of the rapidly increasing volume of data about the Earth. Volume highlights include: An introduction to the breadth of big earth data analytics Architectures developed to support big earth data analytics Different analysis and statistical methods for big earth data Current applications of analytics to Earth science data Challenges to fully implementing big data analytics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more in this Q&A with the editors.

Table of Contents:
Contributors vii Preface xiii 1 An Introduction to Big Data Analytics 1 Erik Hoel Part I: Big Data Analytics Architecture 29 2 Introduction to Big Data Analytics Architecture 31 Thomas Huang 3 Scaling Big Earth Science Data Systems Via Cloud Computing 35 Hook Hua, Gerald Manipon, and Sujen Shah 4 NOAA Open Data Dissemination (Formerly NOAA Big Data Project/Program) 65 Adrienne Simonson, Otis Brown, Jenny Dissen, Edward J. Kearns, Kate Szura, and Jonathan Brannock 5 A Data Cube Architecture for Cloud-Based Earth Observation Analytics 95 Peter Wang, Robert Woodcock, Ronnie Taib, Matt Paget, and Alex Held 6 Open Source Exploratory Analysis of Big Earth Data With Nexus 115 Thomas Huang, Edward M. Armstrong, Nga T. Chung, Eamon Ford, rank R. Greguska III, Joseph C. Jacob, Brian D. Wilson, Elizabeth Yam, and Alice Yepremyan 7 Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations 137 Christopher Lynnes, Michael M. Little, Thomas Huang, Joseph Charles Jacob, Chaowei Phil Yang, Mahabaleshwara Hegde, and Hailiang Zhang Part II: Analysis Methods for Big Earth Data 153 8 Introduction to Analysis Methods for Big Earth Data 155 Christopher Lynnes 9 Spatial Statistics for Big Data Analytics in the Ocean and Atmosphere: Perspectives, Challenges, and Opportunities 159 Kevin A. Butler and Tiffany C. Vance 10 Giving Scientists Back Their Flow: Analyzing Big Geoscience Data Sets in the Cloud 177 Niall Robinson, Theo McCaie, Jacob Tomlinson, Alex Hilson, Tom Powell, Rachel Prudden, Megan Fitzsimon, and Alberto Arribas 11 The Distributed Oceanographic Match-Up Service 195 Shawn R. Smith, Mark A. Bourassa, Jocelyn Elya, Thomas Huang, Kevin Michael Gill, Frank R. Greguska III, Nga Chung, Vardis Tsontos, Benjamin Holt, Thomas Cram, and Zaihua Ji Part III: Big Earth Data Applications 221 12 Introduction to Big Earth Data Applications 223 Christopher Lynnes and Tiffany C. Vance 13 Topological Methods for Pattern Detection in Climate Data 227 Grzegorz Muszynski, Vitaliy Kurlin, Dmitriy Morozov, Michael Wehner, Karthik Kashinath, and Prabhat Ram 14 Exploring Large Scale Data Analysis and Visualization for Atmospheric Radiation Measurement Data Discovery Using NoSQL Technologies 243 Bhargavi Krishna, Kyle Dumas, and Giri Prakash 15 Demonstrating Condensed Massive Satellite Data Sets for Rapid Data Exploration: The MODIS Land Surface Temperatures of Antarctica 259 G. E. Grant, D. W. Gallaher, and Q. Lv 16 Developing Big Data Infrastructure for Analyzing AIS Vessel Tracking Data on a Global Scale 279 Rob Bochenek, Jessica Austin, John-Marc Dunaway, and Tiffany C. Vance 17 Future of Big Earth Data Analytics 299 Christopher Lynnes and Thomas Huang Index 311


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Product Details
  • ISBN-13: 9781119467571
  • Publisher: John Wiley & Sons Inc
  • Binding: Hardback
  • Language: English
  • Returnable: N
  • Spine Width: 28 mm
  • Width: 160 mm
  • ISBN-10: 1119467578
  • Publisher Date: 22 Nov 2022
  • Height: 226 mm
  • No of Pages: 352
  • Returnable: N
  • Weight: 522 gr


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