FRACTAL ANALYSIS FOR OIL SPILLS CLUSTERING IN AHOADA COMMUNITIES OF THE NIGER DELTA REGION OF NIGERIA

• Main Authors: Umar, H. A., Abdul Khanan, M. F., Magashi, S. B., Ja’afar, M. M., Sani, M. J.
• Format: Conference Proceeding
• Language: English
• Subjects: Analysis; Basic converters; Clustering; Density; Dimensions; Distance; Distribution; Fractal analysis; Fractal geometry; Fractals; Kernels; Oil spills; Rivers
• ISSN: 2194-9034; 1682-1750; 2194-9034
• DOI: 10.5194/isprs-archives-XLVIII-4-W6-2022-371-2023

This study uses fractal analysis to understand how oil spills are clustered at different scales in Ahoada communities of the Niger Delta region of Nigeria. The ArcGIS software was used in designing the hotspot map of the study area using Kernel density estimation. Results of spatial spill distribution from the Kernel density revealed that Bayelsa, Rivers, and Delta states are the hottest spots for oil spill occurrences and distribution and communities within the Rivers state including Ochebeke, Ukperede, Odieke and Akinima has been widely affected by the spills. The box counting method was employed for understanding clustering associated with oil spills in the area using ArcGIS interface. The method uses the conversion tool embedded in ArcGIS to convert oil spills points into raster. A basic analysis of this fractal plot suggest a dual fractal analysis for oil spill occurrences within the study location. This is evident by a low fractal dimension of 0.419 at distances of 1.1 km. At higher distances above 1.1 km, oil spill occurrences are characterised by a fractal dimension of 1.411. According to the fractal plot, regional and local fractal for oil spill occurrences is defined by a threshold distance of 1.2 km. At scales less than 1.2 km, oil spill occurrences exhibit a fractal dimension of 0.063 while at scales above this distance, the occurrences of oil spill are defined by a fractal of 1.249. A general analysis of fractal for both oil spill types suggests a small fractal dimension values and a more discrete scale compared to the regional scale. The relative low fractal dimension values at discrete scale suggest a high clustering of oil spill locations. This study gives a relative idea about the clustering tendency. This would enable proper remediation to be carried out in the area.