Submit your papersSubmit Now
For Enquiries: [email protected]
IIARD LogoIIARD

A GIS-Based Impact Assessment of the December 1 , 2024 Reported Oil Spill and Fire Incident at the NNPC Eighteen Operating Ltd in Buguma, Degema Local Government Area of Rivers State Nigeria

Oluchi L. U., Adamu C.J., Isah C. Y., Bello I.E., Mustapha A.

Abstract

Oil spills and associated fire incidents are recurrent environmental challenges in the Niger Delta, with severe ecological and public health implications. However, most reported impacts lack empirical, geospatial evidence. On December 1, 2024, an oil spill and fire occurred at NNPC Eighteen Operating Ltd , Buguma, Degema LGA, Rivers State. This study applied geospatial techniques to assess the extent of environmental damage and provide evidence-based insights for decision-making. Synthetic Aperture Radar (Sentinel-1) and Optical (Sentinel-2) satellite imageries covering pre- and post-incident periods (November 17, 2024–February 6, 2025) were analyzed. Standard preprocessing techniques, including calibration, speckle filtering, geo-referencing, and masking, were applied. The Normalized Difference Vegetation Index was computed to quantify vegetation health, while the Normalized Burn Ratio assessed fire severity. Data from the Oil Spill Monitor platform and ground reports informed contextual analysis. The NDVI analysis revealed a 29% decline in vegetation health between November 17, 2024, and January 1, 2025, indicating substantial ecological stress. NBR results showed that approximately 33% of vegetation was severely burnt between November 17 and December 22, 2024, with only marginal improvement observed afterward. Sentinel-1 imagery consistently revealed persistent dark patches in surrounding water bodies, confirming oil contamination. Communities at risk included Bukuma, Obenibokiri, Bekirikiri, Buguma, Abalama Creek, and nearby schools and health facilities. Policymakers and operators should adopt geospatial monitoring (NDVI, NBR, SAR) as a standard in spill response, remediation, and recovery programs. Continuous remote sensing and ground-truth validation are critical for long-term ecosystem monitoring. The integration of SAR and optical analysis provides robust empirical evidence of the oil spill’s ecological impact, demonstrating incomplete recovery of vegetation and persistent contamination. Geospatial technology proves indispensable for transparent impact assessment, community protection, and informed policy formulation.

Keywords

GISOil SpillEnvironmentBugumaNNPCOML IIARD International Journal of Geography & Environmental Management I.

References

Abd El-Kawya, O. R., Rød, J. K., Ismail, H. A., & Suliman, A. S. (2011). Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Applied Geography, 31(2), 483-494. Adamu, B., Ogutu, B., & Tansey, K. (2018). Oil spill detection in Niger Delta using satellite remote sensing technologies. International Journal of Remote Sensing, 39(11), 3514-3536. https://doi.org/10.1080/01431161.2018.1444295 Adamu, B., K. Tansey, & B. Ogutu (2015). “Using Vegetation Spectral Indices to Detect Oil Pollution in the Niger Delta.” Remote Sensing Letters 6 (2): 145–154. doi:10.1080/ 2150704x.2015.1015656. Alpers, W., & Hühnerfuss, H. (1989), 'Radar signatures of oil films floating on the sea surface and the Marangoni effect,' Journal of Geophysical Research, Vol. 94, highlights the typical backscatter values for oil slicks in radar imaging and the damping effects caused by oil. Attema, E., Snoeij, P., Duesmann, B., Davidson, M., Floury, N., Rosich, B., Rommen, B., & Levrini, G. (2010). GMES Sentinel-1 mission and system. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (pp. 175-178). Honolulu, HI, USA. Brekke, C., & Solberg, A. H. S. (2005). Oil spill detection by satellite remote sensing. Remote Sensing of Environment, 95(1), 1-13. https://doi.org/10.1016/j.rse.2004.11.015 Campbell, J. B., & Wynne, R. H. (2011). Introduction to remote sensing (5th ed.). The Guilford Press. Chaturvedi, P., Rao, Y. S., & Panigrahy, S. (2020). Detection of oil spills over the Al Khafji region of the Persian Gulf using SAR imagery. Marine Pollution Bulletin, 150, 110647. https://doi.org/10.1016/j.marpolbul.2019.110647. Copernicus browser (2024), https://browser.dataspace.copernicus.eu/ Fingas, M., Brown, C. E., & Fieldhouse, B. (2018). Review of oil spill remote sensing. Marine Pollution Bulletin, 134, 47-64. https://doi.org/10.1016/j.marpolbul.2017.09.040 Fiscella, B., Giancaspro, A., Nirchio, F., Pavese, P., & Trivero, P. (2000). Oil spill detection using marine SAR images. International Journal of Remote Sensing, 21(18), 3561-3566. https://doi.org/10.1080/014311600750037570 Garcia-Pineda, O., MacDonald, I. R., Li, X., Jackson, C. R., & Pichel, W. G. (2009). Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2(3), 203-209. https://doi.org/10.1109/JSTARS.2009.2033612 Google Earth Pro (Version 7.3.3) [Software]. (2024). Google LLC. https://www.google.com/earth/ Heywood, I., Cornelius, S., & Carver, S. (2011). An introduction to geographical information systems (4th ed.). Pearson Education. Jones, H. G. (2001). Spatial patterns in remote sensing: Looking for changes and differences in imagery. CRC Press. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote sensing and image interpretation (7th ed.). Wiley. Mishra, D. R., H. J. Cho, S. Ghosh, A. Fox, P. B. Christopher Downs, T. Merani, P. Kirui, N. Jackson, & S. Mishra, (2012). “Post-Spill State of the Marsh: Remote Estimation of the Ecological Impact of the Gulf of Mexico Oil Spill on Louisiana Salt Marshes.” Remote Sensing of Environment 118: 176– 185. doi:10.1016/j.rse.2011.11.007. IIARD International Journal of Geography & Environmental Management NOSDRA (2024), https://nosdra.gov.ng Orji, N. (2025, March 6). Reps order NNPCL, NEOL to clean up Buguma Oil Spill. The Sun Newspaper. Retrieved from https://thesun.ng/reps-order-nnpcl-neol-to-clean-up-buguma- oil-spill/ Osuji, L.C. and Onojake, C.M. (2004). Trace Metals Associated with Crude Oil: A Case Study of Ebocha-8 Oil Spill-Polluted Site in Niger Delta, Nigeria, Chemistry and Biodiversity, 1: 1708-1715. http://dx.doi.org.10.1002/cbdv.2004 9 0129. Retrieved April 3, 2024, from https://www.oilspillmonitor.ng Retrieved September 15, 2024, from https://www.geo.university: Oil spill detection with SAR images Schvartzman, I., Havivi, S., Maman, S., Rotman, S. R., and Blumberg, D. G.: LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1183–1186, https://doi.org/10.5194/isprs-archives-XLI-B8-1183-2016, 2016.Mera, D.; Bolon-Canedo, V.; Cotos, J.M.; Alonso-Betanzos, A. On the use of feature selection to improve the detection of sea oil spills in SAR images. Comput. Geosci. 2017, 100, 166–178. Solberg, A. H. S., Brekke, C., & Husøy, P. O. (2007). Oil spill detection in Radarsat and Envisat SAR images. IEEE Transactions on Geoscience and Remote Sensing, 45(3), 746-755. https://doi.org/10.1109/TGRS.2007.890243. Topouzelis, K. N. (2008). Oil spill detection by SAR images: Dark formation detection, feature extraction, and classification algorithms. Sensors, 8(10), 6642-6659. https://doi.org/10.3390/s8106642 Tufte, L., Meyer, P., Wesche, C., Reimer, B., & Skøelv, A. (2022). Using air- and spaceborne remote sensing data for the operational oil spill monitoring of the German North Sea and Baltic Sea. Marine Pollution Bulletin, 183, 114025. https://doi.org/10.1016/j.marpolbul.2022.114025 UNITAR. (n.d.). Introduction to remote sensing [PDF file]. UNOSAT NGA2201 training module. Retrieved from file:///C:/UNITAR/UNOSAT_NGA2201/PPT/Module%203a%20Introduction%20to%20 Remote%20Sensing.pdf Zhang, Y.; Li, H.; Wang, X.; Dan, W. Edge extraction of marine oil spill in SAR images. In Proceedings of the 2010 International Conference on Challenges in Environmental Science and Computer Engineering , Wuhan, China, 6–7 March 2010; pp. 439–442.

More Articles from IIARD INTERNATIONAL JOURNAL OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT