This presentation will demonstrate how GIS can integrate user data from the SAF-T-Net app, National Weather Service, U.S. Census Bureau, and Emergency Managers in the state of Alabama. Geographic Information Systems (GIS) software is a powerful platform to integrate social and scientific data involved in the warning process. Geostatistical techniques including cluster, hot spot, and density analysis were used to spatially identify areas that are under-represented based on SAF-T-Net use. Social vulnerability is a measure of an individual's susceptibility to danger and harm in the event severe weather events. By including social data, the pattern of spatial coverage of warnings as related to social vulnerability was assessed. The work demonstrates both general findings for the entire state, as well as case studies of specific severe events.
Results found from this research provide insight into where users are located, how and when they receive warnings, and what sociospatial factors influence their decision making process in a severe event. This information can improve communication between forecasters, decision makers, and the public, which will save lives and property in the future.