Data Science Applied to Sustainability Analysis
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Product details:
- Publisher Elsevier Science
- Date of Publication 17 May 2021
- ISBN 9780128179765
- Binding Paperback
- No. of pages310 pages
- Size 234x190 mm
- Weight 660 g
- Language English 104
Categories
Long description:
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.
MoreTable of Contents:
I. Introduction
1. Overview of Data Science and Sustainability Analysis and State of their Co-Application
II. Enironmental Health and Sustainability
2. Applying AI for Conservation
3. Water balance characterization
4. Machine Learning in the Australian Critical Zone
III. Energy and Water
5. A Clustering Analysis of Energy and Water Consumption in U.S. States from 1985 to 2015
6. Energy footprint of big data evaluated with data science
7. Solar PV rooftop disaprities by race and ethnicity in US
8. Screening materials for solar pv
IV. Sustainable Systems Analysis
9. Machine Learning in life cycle analysis
10. Industry sustainable supply chain management with data science
V. Society and Policy
11. Machine Learning to Inform Enhance Environmental Enforcement
12. Sociologically informed use of remote sensing data to predict rural household poverty
13. Trade-offs Between Environmental and Social Indicators of Sustainability
VI. Conclusion
14. Research and Development for Increased Application of Data Science in Sustainability analysis
