Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

Ashutosh Kumar Dubey, Abhishek Kumar, Sushil Kumar Narang, Moonis Ali Khan, Arun Lal Srivastav

• Publisher: Elsevier
• Year: 2022
• ISBN:
  9780323997157
• Topic: Physical Sciences
• Subtopic: Meteorology & Climatology

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.

• Includes case studies on the application of AI and machine learning for monitoring climate change effects and management
• Features applications of software and algorithms for modeling and forecasting climate change
• Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

Table of contents

• Cover Image
• Title Page
• Copyright
• Table of Contents
• Contributors
• Chapter 1 Climate uncertainties and biodiversity: An overview
• Chapter 2 Historical perspectives on climate change and its influence on nature
• Chapter 3 Impact of climate change on water quality and its assessment
• Chapter 4 Climate change impacts on water resources: An overview
• Chapter 5 Impact of plastics in the socio-economic disaster of pollution and climate change: The roadblocks of sustainability in India
• Chapter 6 Impression of climatic variation on flora, fauna, and human being: A present state of art
• Chapter 7 Impact of air quality as a component of climate change on biodiversity-based ecosystem services
• Chapter 8 Role of climate change in disasters occurrences: Forecasting and management options
• Chapter 9 Forecasting and management of disasters triggered by climate change
• Chapter 10 El-Niño Southern Oscillation and its effects
• Chapter 11 Impact of socioeconomic parameters on adoption of climate resilient technology under varying vulnerability conditions: Evidences from Himalayan region
• Chapter 12 Artificial intelligence/machine learning techniques in hydroclimatology: A demonstration of deep learning for future assessment of stream flow under climate change
• Chapter 13 The role of artificial intelligence strategies to mitigate abiotic stress and climate change in crop production
• Chapter 14 Application of artificial intelligence in environmental sustainability and climate change
• Chapter 15 Machine learning approach for climate change impact assessment in agricultural production
• Chapter 16 Climate change: Prediction of solar radiation using advanced machine learning techniques
• Chapter 17 Concept of climate smart villages using artificial intelligence/machine learning
• Chapter 18 Significance of artificial intelligence to develop mitigation strategies against climate change in accordance with sustainable development goal (climate action)
• Chapter 19 A cross-sectional study about the impacts of climate change on living organisms: A case study of Odisha province of India
• Chapter 20 Development of mitigation strategies for the climate change using artificial intelligence to attain sustainability
• Chapter 21 Role of artificial intelligence in environmental sustainability
• Index