Adamu, Bashir; Tansey, Kevin; Ogutu, Booker (2015). Using vegetation spectral indices to detect oil pollution in the Niger Delta. REMOTE SENSING LETTERS, 6(2), 145-154.

Abstract
Vegetation health and vigour may be affected by oil leakage or pollution. This effect can alter a plant's behaviour and may be used as evidence for detecting oil pollution in the environment. Satellite remote sensing has been shown to be an effective tool and approach to detect and monitor vegetation health and status in polluted areas. Previous research has used vegetation indices derived from remotely sensed satellite data to monitor vegetation health. This study investigated the potential for using broadband multispectral vegetation indices to detect impacts of oil pollution on vegetation conditions. Twenty indices were explored and evaluated in this study. The indices use data acquired at the visible, near infrared and shortwave infrared wavelengths. Comparative index values from the 37 oil polluted and non-polluted (control) sites show that 12 Broadband multispectral vegetation indices (BMVIs) indicated significant differences (p-value<0.05) between pre- and post-spill observations. The 12 BMVI values at the polluted sites before and after the spill are significantly different with the ones obtained on the spill event date. The result at the non-polluted (control) sites shows that 11 of the 20 BMVI values did not indicate significant change and remained statistically invariant before and after the spill date (p-value>0.05). Therefore, it can be stated that, in this study, oil spills seem to result in biophysical and biochemical alteration of the vegetation, leading to changes in reflectance signature detected by these indices. Five spectral indices (normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), adjusted resistant vegetation index (ARVI2), green near infrared (G/NIR) and green shortwave infrared (G/SWIR)) were found to be consistently sensitive to the effects of oil pollution on vegetation and hence could be used to map and monitor oil pollution in vegetated areas.

DOI:
10.1080/2150704X.2015.1015656

ISSN:
2150-704X