e-Research: A Journal of Undergraduate Work
This paper focuses on the detection of oil spills using satellite information. ��For this research project, the focus will be primarily on the Deepwater Horizon Oil Spill, which is the largest accidental oil spill. In order to detect an oil spill, the chlorophyll a content must be observed with data from the SeaWiFs at 9km and the MODIS-aqua at 9km and 4km. There is conflicting evidence of whether or not chlorophyll a concentration is positively correlated with the presence of an oil spill. This will be further investigated in the experiment. Also, by utilizing the MODIS instrument aboard the terra and aqua satellites, the amount of solar radiation during the day can be measured, particularly at the wavelength 443nm. Also related to the reflectance of the area of the oil spill is the sea surface temperature. The sea surface temperature can be measured by the MODIS-aqua and MODIS-terra at 9km during the day and night. It is hypothesized that high levels of dissolved organic matter also suggest the presence of an oil spill. Measurements from the SeaWiFs at 9km and the MODIS-aqua at 9km and 4km can be analyzed to show the levels of dissolved organic matter. The measurements of these specific parameters help to detect oil spills as well as to show the effects that oil spills have on the surrounding environment.� For this study, measurements from these satellites over the Gulf of Mexico are taken before, during, and after the occurrence of the Deepwater Horizon Oil Spill that occurred between April and July 2010.� These measurements show that there are positive correlations between the presence of an oil spill and both the chlorophyll a concentration and reflectance of the oil spill. In contrast, sea surface temperature was found to be lower in the area of the oil spill. Evidence from colored dissolved organic matter in the affected area proved to be inconclusive.
"Utilizing Remote Sensing to Detect Deepwater Horizon Oil Spill Properties,"
e-Research: A Journal of Undergraduate Work: Vol. 2:
2, Article 7.
Available at: https://digitalcommons.chapman.edu/e-Research/vol2/iss2/7
Environmental Indicators and Impact Assessment Commons, Oceanography Commons, Remote Sensing Commons