This is an article from the Summer 2015 VPS. For more VPS articles, click here
Hottest 30 percent daily surface temperature averages per census tract mapped by percent occurrence throughout season. Points represent survey responses where participant doesn’t use air conditioning due to cost. Image Credit: Arizona Health and Air Quality Team
Category:åÊAnalyzing Human and Environmental Health
Project Team: Arizona Health & Air Quality
Team Location: NASA Langley Research Center – Hampton, Virginia
Authors:
Amy Stuyvesant
Geordi Alm
Rocky Garcia
Emma Baghel
April Rascon
Bernardo Gracia
Mentors/Advisors:
Dr. David Hondula (Arizona State University)
Dr. Kenton Ross (NASA DEVELOP National Program)
Abstract:
Extreme heat causes more human fatalities in the United States than any other natural disaster, elevating the concern of heat-related mortality. Maricopa County, Arizona, is known for its high heat index and is the leading megapolitan area in the U.S. for population growth and urbanization. As Phoenix expands, the increase in urban structures raises nighttime temperatures and induces a positive feedback loop, creating an urban heat island (UHI) effect. Individuals at higher risk are unequally distributed, leaving the poor, homeless, non-native English speakers, elderly, and socially isolated vulnerable to heat events. While this is a devastating incidence, it can be prevented. The Arizona Department of Health Services and the Phoenix Heat Relief Network are among those working to create more effectively placed cooling centers and heat warning systems to aid those with the highest exposure. Using NASA Earth observation technology from Landsat 8, Aqua (MODIS), and Terra (ASTER) satellites (sensors) the daily spatial and temperature variability within the UHI was quantified over the summer seasons of 2005-2014. A series of one-way analysis of variance (ANOVA) revealed significant differences between daily surface temperature averages of the hottest 30 percent of census tracts within a single season. Visual analyses displayed shifts of where and how consistently the top 30 percent occur. These results provided detailed information regarding nuances within the UHI effect and will allow pertinent recommendations regarding the health department’s adaptive capacity. They also hold essential components for future policy regarding appropriate locations for cooling centers and efficient warning systems.