Abstract
The Miami International Airport thermometer can read a high of 87°F on any given summer day. Yet the combination of humidity, concrete structures in close proximity, and lack of shade lend to a more torturous ‘real feel’ easily exceeding triple digits for anyone working on the tarmac. As the extreme heat events in America incrementally grow in duration and severity every year, the need for policy development matches pace with decreasing negative impacts for vulnerable populations. Through mapping, data source research, relevant report reviews and policy identification, this project was to provide updated materials for the University of Miami Office of Civic and Community Engagement’s existing Miami Affordability Project (2015) and corresponding Climate Policy Toolkit which seeks to promote resiliency programs.
As data collection ensued, it became obvious that some desired variables for analysis were not available. Due to privacy laws, heat-related health incidences are not known and present data is scant at best as medical classifications do not differentiate heat illnesses especially for mapping purposes. Also, clarity of vulnerable populations is best represented through a number of census statistic variables for mapping extreme heat vulnerability.
Through GIS mapping, corresponding datasets were analyzed for spatial relationships of determined variables. Spatial autocorrelation Global Moran’s I result identified the normal distribution of Miami’s surface heat giving credit to the less than 1% chance the clustered pattern is random. Continued from there, the Hot Spot analysis acknowledged locales of clustered assisted housing units in expected locations. Overwhelmingly, vulnerable populations live where it is hotter than the mean surface temperature.
Through the Geographically Weighted Regression analysis, the results clarified that the most correlated variables providing good prediction of surface temperatures are percent of households living below the poverty level and the number of households who have central air conditioning per census tracts. These analyses lend to the ability for community leaders to direct action efficiency with respect to the necessary policies needed for positive social change.