Obinna C.D. Anejionu
Lancaster Environment Centre
· M.Sc. GIS with Remote Sensing, University of Greenwich - Sept 2007 - Oct 2008.
· M.Sc. Hydrographic Surveying, University of Nigeria Nsukka - Jan 2005 - Sept 2007.
· B.Sc. Geoinformatics and Surveying, University of Nigeria Nsukka - Apr 1998 – Aug 2003.
2010 – Present. Lecturer II, Department of Geoinformatics and Surveying, University of Nigeria Enugu Campus
2009 – 2010. Assistant Lecturer, Department of Geoinformatics and Surveying, University of Nigeria Enugu Campus
2006 – 2009. Graduate Assistant, Department of Geoinformatics and Surveying, University of Nigeria Enugu Campus
REMOTE SURVEYS OF GAS FLARING AND MODELLING OF THE ENVIRONMENTAL AND HEALTH IMPACTS IN THE NIGER DELTA
The Niger Delta region of Nigeria contains some of the most endangered ecosystems in the world due to pollution arising from oil and gas activities in the region. Gas flaring has been identified as a major contributor to the overall environmental pollution in the region. There are strong indications that flaring has caused widespread air pollution, heat stress, acid rain, and soil bacteria reduction. However, the specific environmental and health impacts of the continuous flaring of gas in the region have been the subject of much debate and speculation. Previous efforts made to evaluate the magnitude of the impact on the surrounding environment have been severely hampered due to lack of sufficient information on the location of the flares and flaring volume, as flaring usually occurs at remote and hazardous locations, with restricted access. Furthermore, public reporting of gas flaring volumes is usually discouraged through bureaucratic bottlenecks. Accurate identification of active flares is a prerequisite to modelling the impact of flares on the ecosystem. Earlier attempts made at identifying gas flares through remote sensing have been based on visual identification of flares from satellite images such as NOAA AVHRR and DMSP OLS; these approaches were limited by issues such as non-automatic detection of flares and misidentification or non discrimination of flares especially amidst other sources of lights (urban lights and biomass fires). This research is seeking to solve this problem by primarily developing reliable remote sensing techniques that will automatically detect flares, and estimate the quantity of gas flared from each source; consequently evaluating the environmental impacts. The specific objectives are to produce a comprehensive spatial inventory of flares for an extended time series; to estimate the flare volumes at the various flow stations; to model air pollution from the flares and produce a series of pollution maps of the Niger Delta; and to model the overall impact of the pollutants on the various aspects of the ecosystem. The methods used so far have involved the determination of appropriate techniques for combinations of three Landsat bands (4, 7, and 6), which have demonstrated capabilities of detecting flares. The work has focussed on determining empirically the optimum threshold values for the discrimination of flares from detectable false alarms such as forest fires, sun glint, and hot natural and anthropogenic surfaces. A problematic issue encountered so far has been the spatial offsets between the various bands, which have been minimised through the spatial buffering of identified potential flares in one of the bands before passing it through another stage of the process. Preliminary results have demonstrated the capability of the techniques to accurately identify locations of active onshore and offshore flares. However, improvements in the techniques are being investigated in order to make the approach more robust and minimise errors of commission and omission, through temporal persistence analysis. Furthermore, ongoing work is developing techniques for the estimation of flare volume, through the fusion of the outputs from the analysis of Landsat data with information derived from MODIS, AVHRR, MSG/SEVIRI and DMSP data.
APPLICATIONS OF GIS AND REMOTE SENSING TECHNIQUES IN EPIDEMIOLOGY: GEOSPATIAL ANALYSIS OF SPATIAL DISTRIBUTION AND ENVIRONMENTAL CODITIONS OF POSSIBLE HABITATS OF EBOLA AND MARBURG VIRUSES IN SUB-SAHARAN AFRICA
Viral haemorrhagic fevers are among the most prominent diseases that have plagued humanity. Among the most notorious of haemorrhagic fevers are Ebola and Marburg, which are two highly infectious and deadly diseases that have appeared sporadically in some parts of Africa, causing many epidemics that have led to the deaths of people and nonhuman primates, in Sub-Saharan Africa. Research are ongoing to identify the natural reservoir of the viruses, which is expected to lead to a better understanding of the viruses, and subsequently to the development of possible cure for them, or establishment of preventive measures against future occurrences. This research was carried out to provide a broader knowledge of filoviruses in Africa, by characterising environmental conditions associated with the breeding of the viruses, and subsequently model the distribution of the viruses. Remote sensing and GIS techniques, such as, unsupervised classification, Normalised Difference Vegetation Index (NDVI), band ratios, reclassification, and map overlay, were employed in this research. The result obtained from the various analyses carried out in this research, identified some locations in and outside Africa as possible habitats of filoviruses, although the natural reservoir of the virus was not identified. It is believed that the results obtained from this research have extended the knowledge in the quest for the identification of the natural reservoir of the two deadly viruses.
Anejionu, C.D.O., Blackburn, G.A., and Whyatt, J.D. (2011). Remote survey of gas flaring in the Niger Delta region of Nigeria with Landsat imagery. Remote Sensing and Photogrammetry Society Annual Conference and AGM, Technical Proceedings. "Earth Observation in a Changing World", 13th -15th September, 2011, Bournemouth University, United Kingdom.
Anejionu, C.D. O. and Ojinnaka, O.C. (2011). Underwater acoustics and depth uncertainties in the tropics. International Hydrographic Review, No. 5., pp14-23. http://www.iho.int/mtg_docs/IHReview/2011/IHR_May192011.pdf
Anejionu, C.D.O., and Okeke, F. I. (in press). Modelling nonpoint source pollution of the southern section of Enugu State through GIS and Remote Sensing. (Accepted by for publication by Journal of the Tropical Environment).
Anejionu, C.D.O., Moka, E.C., and Ndukwu, R.I. (2011). Design and development of surveying computational software for land reform administration. Nigerian Instiution of Surveyors, 46th Annual General Meeting & Conference, Technical Proceedings, "Land Reforms in Nigeria: Issues and Challenges", 13th -17th June, 2011, Cultural Centre Complex, Calabar, Cross - River State. Nigeria.
Anejionu, C.D.O., Anejionu, M.G.U. (2011). Modelling the Spatial distribution of Ebola and Marburg diseases in Sub-Saharan Africa through GIS and Remote Sensing. Journal of Environmental Management and Safety. Vol 2 No 2. P42-84. Enugu, Nigeria.
Nnam, V.C., Okeke, F.I., and Anejionu, C.D. O. (2011). Implementation of a Multipurpose Cadastre in Nigeria: A Case Study of Achara Layout, Enugu State Nigerian Instiution of Surveyors, 46th Annual General Meeting & Conference, Technical Proceedings, "Land Reforms in Nigeria: Issues and Challenges", 13th -17th June, 2011, Cultural Centre Complex, Calabar, Cross - River State. Nigeria.
Okeke, F. I. and Anejionu, C.D.O. (2007). Investigation of the usefulness of fusing NigeriaSat-1 and other remote sensing images as well as High-Resolution Aerial Photographs. The Nigerian Journal of Space Research, Vol. 4. P. 73-79. Nsukka Nigeria.
· Anejionu C.D.O. 2010. Applications of GIS and Remote Sensing in epidemiology: Geospatial analysis of the spatial distribution and environmental conditions of possible habitats of Ebola and Marburg viruses in Sub Saharan Africa. VDM Verlag Dr. Müller, Saarbrücken. ISBN: 9783639257090. Germany.