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Book Synopsis

Chapter 1. Artificial Intelligence and Machine Learning for Climate Disaster Management.- Chapter 2. The Climate Science, designing, and implementation of Climate Policy.- Chapter 3. Strategic Integration of Green Innovation and Information Systems for Sustainable Development.- Chapter 4. Artificial Intelligence and Machine Learning to Assess the Effects of COVID-19 on Land Surface Temperature (LST) and Air Quality Index.- Chapter 5. Trend analysis of long-term temperature data for prediction of heat waves through statistical analysis using extreme value theory for climate disaster management.- Chapter 6. Risk Assessment and Vulnerability Mapping of Soil Erosion for Climate  Resilient Disaster Management with Geospatial Techniques.- Chapter 7. A Geospatial approach for DEM-Based Surface Hydrological Modelling of Sub-Watersheds towards Climate Disaster Management.- Chapter 8. Urban Heat Island Mitigation through Green Infrastructure for Sustainable Development.- Chapter 9. Identification of soil erosion susceptible areas with analytical hierarchy process (AHP) modelling for climate disaster management.- Chapter 10. Role of Artificial Intelligence and Machine Learning for Climate Disaster Management and Earth Resource Management.- Chapter 11. From Data to Planning: Innovations through LiDAR technology and data science in Sustainable Urban Resource Management.- Chapter 12. Beyond the Office Walls: Exploring Nature Connectedness for Climate Stress and Disaster Management.- Chapter 13. Challenges and Future Trends in Climate Disaster Management.

Artificial Intelligence and Machine Learning for Climate Disaster Management

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      Publisher: Springer
      Publication Date: Publication Date: 11/4/2025
      ISBN13: 9789819515875, 978-9819515875
      ISBN10: 9819515874
      Also in:
      Ecological science, the Biosphere

      Description

      Book Synopsis

      Chapter 1. Artificial Intelligence and Machine Learning for Climate Disaster Management.- Chapter 2. The Climate Science, designing, and implementation of Climate Policy.- Chapter 3. Strategic Integration of Green Innovation and Information Systems for Sustainable Development.- Chapter 4. Artificial Intelligence and Machine Learning to Assess the Effects of COVID-19 on Land Surface Temperature (LST) and Air Quality Index.- Chapter 5. Trend analysis of long-term temperature data for prediction of heat waves through statistical analysis using extreme value theory for climate disaster management.- Chapter 6. Risk Assessment and Vulnerability Mapping of Soil Erosion for Climate  Resilient Disaster Management with Geospatial Techniques.- Chapter 7. A Geospatial approach for DEM-Based Surface Hydrological Modelling of Sub-Watersheds towards Climate Disaster Management.- Chapter 8. Urban Heat Island Mitigation through Green Infrastructure for Sustainable Development.- Chapter 9. Identification of soil erosion susceptible areas with analytical hierarchy process (AHP) modelling for climate disaster management.- Chapter 10. Role of Artificial Intelligence and Machine Learning for Climate Disaster Management and Earth Resource Management.- Chapter 11. From Data to Planning: Innovations through LiDAR technology and data science in Sustainable Urban Resource Management.- Chapter 12. Beyond the Office Walls: Exploring Nature Connectedness for Climate Stress and Disaster Management.- Chapter 13. Challenges and Future Trends in Climate Disaster Management.

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