Human and environmental exposure to hydrocarbon pollution in the Niger Delta:A geospatial approach

This study undertook an integrated geospatial assessment of human and environmental exposure to oil pollution in the Niger Delta using primary and secondary spatial data. This thesis begins by presenting a clear rationale for the study of extensive oil pollution in the Niger Delta, followed by a critical literature review of the potential application of geospatial techniques for monitoring and managing the problem. Three analytical chapters report on the methodological developments and applications of geospatial techniques that contribute to achieving the aim of the study. Firstly, a quantitative assessment of human and environmental exposure to oil pollution in the Niger Delta was performed using a government spill database. This was carried out using Spatial Analysis along Networks (SANET), a geostatistical tool, since oil spills in the region tend to follow the linear patterns of the pipelines. Spatial data on pipelines, oil spills, population and land cover data were analysed in order to quantify the extent of human and environmental exposure to oil pollution. The major causes of spills and spatial factors potentially reinforcing reported causes were analysed. Results show extensive general exposure and sabotage as the leading cause of oil pollution in the Niger Delta. Secondly, a method of delineating the river network in the Niger Delta using Sentinel-1 SAR data was developed, as a basis for modelling potential flow of pollutants in the distributary pathways of the network. The cloud penetration capabilities of SAR sensing are particularly valuable for this application since the Niger Delta is notorious for cloud cover. Vector and raster-based river networks derived from Sentinel-1 were compared to alternative river map products including those from the USGS and ESA. This demonstrated the superiority of the Sentinel-1 derived river network, which was subsequently used in a flow routing analysis to demonstrate the potential for understanding oil spill dispersion. Thirdly, the study applied optical remote sensing for indirect detection and mapping of oil spill impacts on vegetation. Multi-temporal Landsat data was used to delineate the spill impact footprint of a notable 2008 oil spill incident in Ogoniland and population exposure was evaluated. The optical data was effective in impact area delineation, demonstrating extensive and long-lasting population exposure to oil pollution. Overall, this study has successfully assembled and produced relevant spatial and attribute data sets and applied integrated geostatistical analytical techniques to understand the distribution and impacts of oil spills in the Niger Delta. The study has revealed the extensive level of human and environmental exposure to hydrocarbon pollution in the Niger Delta and introduced new methods that will be valuable fo

River network delineation from Sentinel 1 SAR data

In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study a new method was developed for delineating river networks using Sentinel-1 imagery. Unsupervised classification was applied to multi-temporal Sentinel-1 data to discriminate water bodies from other land cover types then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available waterbody products from USGS, ESA and OpenStreetMap and a river network derived from a SRTM DEM. From both raster-based and vector-based accuracy assessments it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The resulting geometric river network was used to perform flow routing analysis which is important for a variety of environmental management and planning applications. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries globally where such data are deficient