Detection of potentially gas flaring-related pollution on vegetation cover using remotely sensed data at 11 flaring sites in Rivers State, Nigeria is the emphasis of this research. 21 Landsat 7 Enhanced Thematic Mapper Plus (ETM ), and 4 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) data dated from 21/04/2000 to 05/02/2022 with  3  cloud cover were used. Normalized Differential Vegetation Index (NDVI) was retrieved from corrected Landsat 7 bands (1-4), and Landsat 8 bands (2-5). Corrected thermal band was used for the computation of Land Surface Temperature (LST). Change in NDVI (δNDVI450-60)m and LST ( δLST60-450m) were computed. NDVI values at 60 m from the stack show that as the year increases, NDVI values around the stack reduces to almost zero. Linear regression analysis was considered for (δ NDVI450-60)mN against ( δNDVI450-60)mE, (δNDVI450-60)mN against (δNDVI450-60)mS, and (δNDVI450-60)mN against (δNDVI450-60)mW. Only (δNDVI450-60)mN against (δNDVI450-60)mW give statistically significant results at 99 % confidence level (p-value  0.0016). (δNDVI450-60)mN,E,S,W against (δLST60-450)mN,E,S,W were considered and results show positive correlation but statistically insignificant. Based on the results of this research, it can be concluded that flaring-related pollution can be detected on vegetation cover using Landsat 7 and Landsat 8 data in the Niger Delta.

This study aims at the assessment of the effects of environmental factors on vegetation cover at the flaring sites in Rivers State, Nigeria. Twenty one Landsat 7 Enhanced Thematic Mapper Plus (ETM) data, and four Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) data dated from 21/04/2000 to 05/02/2022 with  3  cloud cover were employed to study eleven gas flaring sites. Matrix Laboratory MATLAB code was developed for data processing and analysis. Normalized Differential Vegetation Index (NDVI) was computed from the atmospherically corrected multispectral bands (1-4) for Landsat 7, and bands (2-5) for Landsat 8. Change in NDVI was computed as NDVI450-60)m in the N, E, S and W directions which is the difference between NDVI at 450 m and 60 m distance from the flare stack. The available environmental factors (Facility size, flare stack height and time i.e. year, month and day) were applied to the (NDVI450-60m) in the 4 cardinal directions. Pairwise linear and multiple regression statistical analyses were adopted to investigate the relationships between each of the (NDVI450-60)mN, (NDVI450-60)mE, (NDVI450-60)mS and (NDVI450-60)mW and facility size, stack height and time. The results show that only 12  of the variance in (NDVI450-60)mN is explained by the available data. Therefore, it can be concluded that the combination of the facility size, flare stack height and time accounted for only 12  of the results. Further researches using the rate and volume of flared gas data, and the vegetation species is required to achieve better results.