Recognizing brownfield prevalence in the United States and globally, researchers strive to better understand brownfields and their climate implications. A brownfield is defined as a property that has a complicated redevelopment or reuse process because of potential hazardous substances, pollutants, or contamination present at the site (EPA 2012). There is a need for brownfield identification on a larger and more effective scale, which can be accomplished with the help of remote sensing data. Brownfields are characteristic to post-industrial areas, where development has fled and the urban core intensity decreases, making Dayton, Ohio the ideal location for brownfield site validation. Brownfields have unique effects on the microclimate and vegetation. These effects in the microclimate allow for the utilization of remote sensing to identify brownfields. Recognizing the importance of high spatial resolution, Sentinel-2 data was used to derive NDVI and emissivity for the validated brownfield sites. Emissivity values of brownfields were found to be statistically significant from urban points and greenspaces. This means that brownfield emissivity values can be used to distinguish them from other features. This research also suggests that brownfields have an effect on the climate, because their emissivity values are higher than greenspaces in Dayton. Overall this research illustrates the potential of remote sensing data to observe microclimatic effects in future research.
Author: Abby Heublein
Faculty Advisor: Jessica McCarty, Geography
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