Heat related illness is the number one cause of human death in relation to extreme weather events in the United States, resulting in an average of 400 deaths per year over the past few decades. It is also expected that both the duration and intensity of these events will increase. The temperature of the surface is measurable from a number of space borne satellites and can be derived using a number of available algorithms. This type of data can be compared to census collected variables to determine the number of persons at risk for heat related morbidity and mortality within urban environments.
Objective
This paper describes a method of determining areas at risk during extreme urban heat events using remote sensing technologies, geographical information systems and artificial neural networks.