Terrestrial Oil spills pose serious health risk to human lives from indirect ingestion of contaminated drinking water, aquatic products and on contaminated farmland produce. Spill impact mapping is essential in establishing the extent of damage by oil spills to inland vegetation. It also helps ascertaining the type of environmental remediation required for a particular landcover. Various detection methods have been reported in the literature's ranging from radiative transfer models, vegetation health indices, canopy water use efficiency and UAVSAR Polarimetric Backscatter Decomposition among several others. These approach in isolation cannot be effectively used in wide area mapping and discrimination of oil free from oil polluted landcover. Similarly, it is also necessary to develop transferable techniques that will leverage freely accessible space borne satellite data for consistent spill impact mapping in near real time. In this study, we integrated derivatives from the freely accessible sentinel 2 spectral reflectance and vegetation health indices, with sentinel 1 retrieved backscatter, alpha (α) and entropy (Η) scatter to examine and map oil spill impacted areas within terrestrial habitat. The utility of machine learning random forest was explored to assess classification accuracies. Initial results suggest that the Red Edge and SWIR Bands of Sentinel 2 are vital discriminators of oil polluted and oil free landcover.
Detection of oil pollution have been evaluated and assessed by several authors adopting such techniques as field spectroscopy, vegetation health indices, canopy water use efficiency and UAVSAR Polarimetric Backscatter and Decomposition among several others. However, no published study at the moment have sought to utilize and assess the potential of Spaceborne Sentinel1 C-Band SAR Datasets in the characterization of vegetation affected by oil pollution. In this study, field work was conducted across 3 sites of a recent, old and a non-polluted site. The field plot center point was used to retrieve image information for the various sites. Effort was made to assess the underlying characteristics of Sentinel -1 C Band derived Entropy and Alpha Plane Polarimetric scatterers and the field spectral responses. Result shows that the Alpha component of the dual polarization decomposition had stable scattering characteristics after the spill compared to the observed random scattering characteristics before the spill. This however indicates a feasible potential of the Alpha plane component scatterers for discerning stressed vegetation as a result of oil pollution.
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