Submitted for Judging
The abundant research examining aspects of social-ecological resilience, vulnerability, and hazards and risk assessment has yielded insights into these concepts but has not produced a convincing approach to measuring community resilience. Quantifying resilience is complicated by several factors including the varying definitions of the term applied in the research, difficulties involved in selecting and aggregating indicators of resilience, and the lack of empirical validation for the indices derived. This App applies a new model, called the Resilience Inference Measurement (RIM) model, to quantify resilience to climate-related hazards in county level for the whole U.S.. The RIM model uses three dimensions (exposure, damage, and recovery indicators) to denote two abilities (vulnerability and adaptability), and employs several data mining methods to derive the resilience rankings, thus enabling validation and inference. The results yielded a high classification accuracy of above 90 percent with 28 predictor variables. The approach is theoretically sound and can be applied to derive resilience indices for different spatial and temporal scales. By the App, the users can directly calculated the resilience index of the places they choose, and view the weightings of the socioeconomic factors that contributes to the resilience scores. The App will not only offer a view of the resilience pattern to the users, but also give them what are the factors that increase or decrease the resilience.