Application of Vegetation Indices for Detection and Monitoring Oil Spills in Ahoada West Local Government Area of Rivers State, Nigeria

The study evaluated the environmental effects of an oil spill in Joinkrama 4 and Akimima Ahoada West LGA, Rivers State, Nigeria, using various vegetation indices. Location data for the spill were obtained from the Nigeria Oil Spill Detection and Response Agency, and Landsat imagery was acquired from the United States Geological Survey. Three soil samples were collected from the affected area, and their analysis included measuring total petroleum hydrocarbons (TPH), total hydrocarbons (THC), and polycyclic aromatic hydrocarbons (PAH). The obtained data were processed with ArcGIS software, utilizing different vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Atmospheric Resistant Vegetation Index (ARVI), Soil Adjusted Vegetation Index (SAVI), Green Short Wave Infrared (GSWIR), and Green Near Infrared (GNIR). Statistical analysis was performed using SPSS and Microsoft Excel. The results consistently indicated a negative impact on the environment resulting from the oil spill. A comparison of spectral reflectance values between the oil spill site and the non-oil spill site showed lower values at the oil spill site across all vegetation indices (NDVI 0.0665-0.2622, ARVI –0.0495-0.1268, SAVI 0.0333-0.1311, GSWIR –0.183-0.0517, GNIR –0.0104-–0.1980), indicating damage to vegetation. Additionally, the study examined the correlation between vegetation indices and environmental parameters associated with the oil spill, revealing significant relationships with TPH, THC, and PAH. A t-test with a significance level of p < 0.05 indicated significantly higher vegetation index values at the non-oil spill site compared to the oil spill site, suggesting a potential disparity in vegetation health between the two areas. Hence, this study emphasizes the harmful effect of oil spills on vegetation and highlights the importance of utilizing vegetation indices and spectral reflectance analysis to detect and monitor the impact of oil spills on vegetation.