Implementation of potential damage assessment tools in hurricane-prone areas is an essential aspect of communicating accurate hurricane risk information. Several indices currently exist (e.g. Saffir-Simpson Hurricane Wind Scale) that are effective communicators storm strength; however, they are unable to quantify potential damage. The recently developed Maina Hurricane Index (MHI) addressed this deficiency and used a hurricane's central minimum pressure and radius of hurricane force winds to create damage forecasts. The development of the MHI involved analyzing data from thirteen historical storms – a small sample size limited by the availability of storm size data. This work revisited the MHI using a larger data set, where results showed that central pressure is the best indicator of potential damage. By creating a single damage value per storm, the MHI aids in the decision making of groups such as insurance companies, yet it does not convey storm impacts of individuals within a community. As a result, this study additionally developed a methodology to generate spatial damage assessments that illustrate the relative damage distribution across a storm. A swath of maximum winds was first generated using a parametric wind field model and then translated to damage using a function based on wind speed and a measure of the directional change in wind. Through the ability to forecast both net damage of land-falling storms and the distribution of damage across the storm, individual perceptions of hurricane risk can be unified and make way for safer preparation and evacuation decisions.