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An investigation into the factors influencing the detectability of oil spills using spectral indices in an oil-polluted environment

Adamu, Bashir, Tansey, Kevin, Ogutu, Booker
International journal of remote sensing 2016 v.37 no.10 pp. 2338-2357
normalized difference vegetation index, oil spills, pollution, regression analysis, remote sensing, vegetation
The aim of this article is to investigate and test the influence of oil spill volume and time gap (number of days between oil spill events and image acquisition date) on normalized difference vegetation index (NDVI) and normalized difference water index (NDWI). This was carried out to determine the effect of these factors on vegetation condition affected by the oil spill. Based on regression analysis, it was shown that increase in the volume of oil spill resulted in increased deterioration of vegetation condition (estimated using NDVI and NDWI) in the study site. The study also tested how the length of time gap between the oil spill and image acquisition date influences the detectability of impacts of oil spill on vegetation. The results showed that the length of time between image acquisition and oil spill influenced the detectability of impacts of oil spill on vegetation condition. The longer the time between the date of image acquisition and the oil spill event, the lower the detectability of impacts of oil spill on vegetation condition. The NDVI seemed to produce better results than the NDWI. In conclusion, time and volume of oil spill can be important factors influencing the detection of pollution using vegetation indices (VIs) in an oil-polluted environment.