Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world.
This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action.
1. Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence - p. i 2. Cover - p. i 3. Front Matter - p. i 4. Title Page - p. iii 5. Copyright - p. iv 6. Table of Contents - p. iv 7. Contributors - p. xvii 8. Chapter 1 Climate uncertainties and biodiversity: An overview - p. 1 9. Chapter 2 Historical perspectives on climate change and its influence on nature - p. 15 10. Chapter 3 Impact of climate change on water quality and its assessment - p. 39 11. Chapter 4 Climate change impacts on water resources: An overview - p. 55 12. Chapter 5 Impact of plastics in the socio-economic disaster of pollution and climate change: The roadblocks of sustainability in India* - p. 77 13. Chapter 6 Impression of climatic variation on flora, fauna, and human being: A present state of art - p. 101 14. Chapter 7 Impact of air quality as a component of climate change on biodiversity-based ecosystem services - p. 123 15. Chapter 8 Role of climate change in disasters occurrences: Forecasting and management options - p. 149 16. Chapter 9 Forecasting and management of disasters triggered by climate change - p. 181 17. Chapter 10 El-Niño Southern Oscillation and its effects - p. 207 18. Chapter 11 Impact of socioeconomic parameters on adoption of climate resilient technology under varying vulnerability conditions: Evidences from Himalayan region - p. 229 19. Chapter 12 Artificial intelligence/machine learning techniques in hydroclimatology: A demonstration of deep learning for future assessment of stream flow under climate change - p. 247 20. Chapter 13 The role of artificial intelligence strategies to mitigate abiotic stress and climate change in crop production - p. 273 21. Chapter 14 Application of artificial intelligence in environmental sustainability and climate change - p. 293 22. Chapter 15 Machine learning approach for climate change impact assessment in agricultural production - p. 317 23. Chapter 16 Climate change: Prediction of solar radiation using advanced machine learning techniques - p. 335 24. Chapter 17 Concept of climate smart villages using artificial intelligence/machine learning - p. 359 25. Chapter 18 Significance of artificial intelligence to develop mitigation strategies against climate change in accordance with sustainable development goal (climate action) - p. 377 26. Chapter 19 A cross-sectional study about the impacts of climate change on living organisms: A case study of Odisha province of India - p. 399 27. Chapter 20 Development of mitigation strategies for the climate change using artificial intelligence to attain sustainability - p. 421 28. Chapter 21 Role of artificial intelligence in environmental sustainability - p. 449 29. Index - p. 469
Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world.
This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action.
1. Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence - p. i 2. Cover - p. i 3. Front Matter - p. i 4. Title Page - p. iii 5. Copyright - p. iv 6. Table of Contents - p. iv 7. Contributors - p. xvii 8. Chapter 1 Climate uncertainties and biodiversity: An overview - p. 1 9. Chapter 2 Historical perspectives on climate change and its influence on nature - p. 15 10. Chapter 3 Impact of climate change on water quality and its assessment - p. 39 11. Chapter 4 Climate change impacts on water resources: An overview - p. 55 12. Chapter 5 Impact of plastics in the socio-economic disaster of pollution and climate change: The roadblocks of sustainability in India* - p. 77 13. Chapter 6 Impression of climatic variation on flora, fauna, and human being: A present state of art - p. 101 14. Chapter 7 Impact of air quality as a component of climate change on biodiversity-based ecosystem services - p. 123 15. Chapter 8 Role of climate change in disasters occurrences: Forecasting and management options - p. 149 16. Chapter 9 Forecasting and management of disasters triggered by climate change - p. 181 17. Chapter 10 El-Niño Southern Oscillation and its effects - p. 207 18. Chapter 11 Impact of socioeconomic parameters on adoption of climate resilient technology under varying vulnerability conditions: Evidences from Himalayan region - p. 229 19. Chapter 12 Artificial intelligence/machine learning techniques in hydroclimatology: A demonstration of deep learning for future assessment of stream flow under climate change - p. 247 20. Chapter 13 The role of artificial intelligence strategies to mitigate abiotic stress and climate change in crop production - p. 273 21. Chapter 14 Application of artificial intelligence in environmental sustainability and climate change - p. 293 22. Chapter 15 Machine learning approach for climate change impact assessment in agricultural production - p. 317 23. Chapter 16 Climate change: Prediction of solar radiation using advanced machine learning techniques - p. 335 24. Chapter 17 Concept of climate smart villages using artificial intelligence/machine learning - p. 359 25. Chapter 18 Significance of artificial intelligence to develop mitigation strategies against climate change in accordance with sustainable development goal (climate action) - p. 377 26. Chapter 19 A cross-sectional study about the impacts of climate change on living organisms: A case study of Odisha province of India - p. 399 27. Chapter 20 Development of mitigation strategies for the climate change using artificial intelligence to attain sustainability - p. 421 28. Chapter 21 Role of artificial intelligence in environmental sustainability - p. 449 29. Index - p. 469
