Interpretable data-driven model for Climate-Induced Disaster damage prediction: The first step in community resilience planning

The frequency and magnitude of Climate-Induced Disasters (CID) have been increasing consistently over the past few decades. Alleviating the impacts of such disasters is thus critically important. Hence, a systematic data-driven framework is developed to predict CID-related damages. The framework encompasses four phases: (1) Data Collection and Fusion, where spatial interpolation methods are employed to integrate data from multiple sources, (2) …