Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Pandey, Ananya Title A name given to the resource Harnessing AI for Environmental Hazard Mitigation and Resilience: Pathways to a Safer Future Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Geostatistical Insights on Mapping Flood Hazards and Wetland Dynamics;pp.151-178 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-3206-2.ch006" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-3206-2.ch006</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105021731585?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105021731585?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pandey A., Christ University, Bangalore, India Description An account of the resource This chapter explores the transformative potential of artificial intelligence (AI) in mitigating environmental hazards and enhancing resilience to climate- related challenges. AI technologies are revolutionizing environmental monitoring, risk assessment, and disaster response through advanced data analytics, machine learning, and predictive modeling. By leveraging AI, stakeholders can predict and mitigate the impacts of natural disasters, improve resource management, and foster resilient infrastructures. The chapter examines the various applications of AI in hazard prediction, such as flood forecasting, wildfire management, and storm tracking, alongside its role in real- time monitoring and adaptive response systems. Furthermore, it highlights the ethical considerations, challenges, and limitations of deploying AI in environmental management. Through case studies and emerging practices, this chapter outlines pathways for harnessing AI to safeguard communities and ecosystems, ensuring a more resilient and sustainable future. 2025 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833733208-6; 979-833733206-2; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online