Exploring Stakeholder Perceptions and Challenges in Leveraging Artificial Intelligence for Land Use and Land Cover Change (LULC) Analysis in Climate Change Mitigation: A Thematic Analysis of Environmental Sustainability Practices

Abstract

This study explores the transformative role of Artificial Intelligence (AI) in climate change mitigation, focusing on its potential to enhance predictive modeling for mitigation strategies and promote environmental justice. AI's ability to process vast amounts of data quickly and accurately enables improved predictive models that forecast land-use changes, climate impacts, and environmental risks. These models play a crucial role in identifying vulnerable areas, monitoring deforestation, tracking urban sprawl, and forecasting the effects of climate change. The study emphasizes how AI can inform more effective and targeted mitigation strategies across sectors such as agriculture, energy, and urban planning. Additionally, the study highlights AI's capacity to support environmental justice by providing marginalized and vulnerable communities with real-time data, empowering them to participate in climate-related decision-making processes. AI's role in identifying communities most at risk of environmental degradation ensures that mitigation efforts address social inequities and promote more inclusive and equitable outcomes. Despite these opportunities, challenges such as data accessibility, infrastructure limitations, and ethical concerns need to be addressed for AI to reach its full potential in climate change mitigation. The study concludes that AI, if deployed responsibly and inclusively, can significantly contribute to sustainable development, enhancing both climate resilience and social equity in the fight against climate change.