AI-Driven Data Analytics for Environmental Decision-Making

This chapter explores the transformative role of AI-driven data analytics in environmental decision-making, addressing its applications, methodologies, and critical challenges. It examines how artificial intelligence enhances environmental monitoring, pollution tracking, biodiversity conservation, and efforts to mitigate climate change. The chapter delves into multimodal data analytics, examining the integration of diverse data sources to provide comprehensive environmental insights. Key challenges, including data quality, scalability, and interpretability, are analyzed alongside ethical considerations, such as privacy and environmental equity. The chapter also presents evaluation metrics for AI-driven environmental systems and explores emerging solutions to improve data quality, model explainability, and governance frameworks. Ultimately, it outlines future directions for AI in environmental decision-making, emphasizing the need for collaborative, responsible approaches that balance technological innovation with ecological sustainability.