AI-Enabled Climate Risk Assessment and Disaster Prediction for Sustainable Development

Abstract

Climate change has increased the frequency and severity of natural disasters, posing significant risks to global sustainability efforts. This paper explores the application of machine learning in climate risk assessment and disaster prediction, utilizing deep learning models, time-series forecasting, and geospatial analysis to detect early warning signals of extreme weather events. We present case studies on AI-driven disaster response systems, highlighting their role in mitigating environmental damage and ensuring resilience in vulnerable communities. The research demonstrates how ML-powered predictive analytics can improve climate adaptation strategies and sustainable urban planning.