Data Science Applied to Sustainability Analysis
eBook - ePub

Data Science Applied to Sustainability Analysis

  1. 310 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Data Science Applied to Sustainability Analysis

About this book

Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses

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Yes, you can access Data Science Applied to Sustainability Analysis by Jennifer Dunn,Prasanna Balaprakash in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Environmental Science. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Title of Book
  2. Cover image
  3. Title page
  4. Table of Contents
  5. Copyright
  6. Table of Contents
  7. Chapter Opener___Chap num. Contributors
  8. Chapter 1 Overview of data science and sustainability analysis
  9. Chapter 2 Applying AI to conservation challenges
  10. Chapter 3 Water balance estimation in Australia through the merging of satellite observations with models
  11. Chapter 4 Machine learning in the Australian critical zone
  12. Chapter 5 A clustering analysis of energy and water consumption in U.S. States from 1985 to 2015
  13. CHAPTER 6 Exploring rooftop solar photovoltaics deployment and energy injustice in the US through a data-driven approach
  14. Chapter 7 Data-driven materials discovery for solar photovoltaics
  15. Chapter 8 Machine learning in life cycle assessment
  16. Chapter 9 Industry sustainable supply chain management with data science
  17. Chapter 10 Deep learning with satellite imagery to enhance environmental enforcement
  18. Chapter 11 Towards achieving the UNs data revolution: combining earth observation and socioeconomic data for geographic targeting of resources for the sustainable development goals
  19. Chapter 12 An indicator-based approach to sustainable management of natural resources
  20. Chapter 13 Research and development for increased application of data science in sustainability analysis
  21. Index