Machine learning prediction of climate-induced disaster property damages considering hazard- and community-related attributes

The rapid increase in the earth’s average temperature has led to an unpreceded surge in the frequency and impacts of Climate-Induced Disaster (CID) across the globe. Subsequently, the costs of CID damages have been growing, and climate action failure and extreme weather events were identified among the most severe global risks over the next decade. Within this context, machine learning-based models are developed to predict CID property damages. …