Remote Sensing of Heat-Related Health Risks: The Trend Toward Coupling Socioeconomic and Remotely Sensed Data

Heat-related death is considered the number one weather-related cause of mortality throughout the world. There is growing concern that, heat waves, the primary meteorological phenomena responsible, will become more intense and numerous in the near future. Provided with this growing hazard the responsibility for mitigation, early detection and warning rests with emergency response agencies as well as academic researchers. Numerous tools exist in the present time to model very complex relationships that truly define vulnerability to such impending disasters. However, compared to other disasters (i.e. flooding, hurricanes, tornadoes, earthquakes, etc.) heat-related effects have not been thoroughly investigated in a geospatial framework. It seems likely that such approaches will provide significant benefit to the vulnerable communities and to policy makers responsible for planning. These approaches involve the usage of multiple sensor data (multi-sensor data fusion) coupled with socioeconomic characteristics to truly capture the fabric of social vulnerability. Evidence is growing that these approaches are beginning to have an impact in forecasting and planning for heat-related health disasters.