Remote Monitoring of the Impact of Oil Spills on Vegetation in the Niger Delta, Nigeria

Kuta, Abdullahi A.; Grebby, Stephen; Boyd, Doreen S.

Abstract

The widespread oil extraction in the Niger Delta and the impacts on different types of vegetation are poorly understood due to lack of ground access. This study aims to determine the impact of oil spills on vegetation in the Niger Delta using a Landsat satellite-derived normalised difference vegetation index (NDVI). The impact of oil spill volume and time after an oil spill on the health of different types of vegetation were evaluated, and the time series of the changes in NDVI were analysed to determine the medium- and long-term responses of vegetation to oil spill exposure, using a combination of linear regression and paired t-tests. With regards to the relationship between spill volume and NDVI, a moderate correlation (R2 = 0.5018) was observed for spill volumes in the range of 401–1000 barrels for sparse vegetation, for volumes greater than 1000 barrels for dense vegetation (R2 = 0.4356), whilst no correlation was found for mangrove vegetation at any range of spill volume. Similarly, the results of the paired t-test confirmed a significant difference (p-value < 0.05) between the change in NDVI values for spill sites and non-spill sites for all vegetation types, with the sparse vegetation being the most affected of the three types. However, the impact of the oil spill on vegetation over a period is not statistically significant. The outcomes of this study provide insights into how different types of vegetation in the Niger Delta respond to oil spills, which could ultimately help in designing an oil spill clean-up program to reduce the impact on the environment.

Citation

Kuta, A. A., Grebby, S., & Boyd, D. S. (2025). Remote Monitoring of the Impact of Oil Spills on Vegetation in the Niger Delta, Nigeria. Applied Sciences, 15(1), Article 338. https://doi.org/10.3390/app15010338

• Journal Article Type: Article
• Acceptance Date: Dec 28, 2024
• Online Publication Date: Jan 1, 2025
• Publication Date: Jan 1, 2025
• Deposit Date: Jan 3, 2025
• Publicly Available Date: Jan 3, 2025
• Journal: Applied Sciences
• Electronic ISSN: 2076-3417
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 15
• Issue: 1
• Article Number: 338
• DOI: https://doi.org/10.3390/app15010338
• Keywords: normalised difference vegetation index (NDVI); vegetation health; vegetation degradation; mangrove; sparse vegetation; dense vegetation; paired t-tests
• Public URL: https://nottingham-repository.worktribe.com/output/43682760
• Publisher URL: https://www.mdpi.com/2076-3417/15/1/338