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This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with < 5% cloud contamination were considered. All the sites are located within a single Landsat scene (Path 188, Row 057). Dark Object Subtraction (DOS) method and Atmospheric Correction Parameter (ATMCORR) Calculator were used to obtain atmospheric correction effects parameters for multispectral and thermal bands [Upwelling radiance (L u), downwelling radiance (L d) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The L u , L d and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (L λ) with the ε values obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.

This study examines the importance of ground validation to Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) observations at 2 gas flaring sites in Rivers State, Niger Delta, Nigeria. 12 Landsat imagery (3 Landsat 5 TM and 9 Landsat 7 ETM+) data acquired from 25/03/1987 to 08/03/2013 with < 5 % cloud contamination were used. Both sites are located within a single Landsat scene (Path 188, Row 057). Ground measurements and observations at both sites took place from (04/08/2012-21/09/2012) and (05/08/2019-22/09/2019). Parameters measured are coordinates of points and features, air temperature and relative humidity; and photographs of locations and features were taken. Both air temperature and relative humidity were measured at 3 different levels above the ground surface at 1 minute interval. The results show that the locational error of points and features from Landsat data and fieldwork measurements give negligible difference of 1.0 × 10-6 to 7.3 × 10-6. Also, 4 classes of land use and land cover (LULC) types retrieved from Landsat data are the same with those observed on site during ground measurements. The air temperature (AT) recorded and Land Surface Temperature (LST) retrieved from Landsat data for both sites show that the closer the distance to the flare, the higher the temperature and vice versa. Results show that the spatial variability in ground AT and derived LST from Landsat data differs within 0.8 to 6.0 K because AT is different from LST. Based on the results acquired, it can be concluded that ground validation is essential and required for maximum utilization and exploitation of remote sensing technology applications.

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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.