Delineation of Soil Erosion Potential (SEP) using GIS and Multiple Influencing Factor (MIF): Case of Ado-Ekiti and Environs
Keywords:
Remotely Sensed Data, GIS, MIF Processes, Weighted Overlay, Soil Erosion Potential.Abstract
Erosion is a serious ecological problem worldwide, and a prominent geo-hazard phenomenon in a typical urban area with high population growth and high rainfall intensity. The aim of this study is to delineate erosion potential zones of Ado Ekiti and its environs using integrated GIS and multiple influencing factors (MIF). The study acquired administrative map of Ekiti state, Landsat-8 OLI, SRTM DEM, geological and soil maps. Bands 2 – 7 and 9 were stacked, haze reduced, orthorectified and optimum index factor (OIF) analysis carried out. Bands 754 (OIF=50.01) were selected for land use land cover image classification while band 7 was subjected to PCI Geomatica and Rockworks software automatic lineament mapping and Rose diagram creation. NDVI was developed using raster calculator on bands 4 and 5 representing Red and Near-Infrared. Slope map was generated from sink filled. Lithological units and soil associations were produced from geological and soil maps through scanning, georeferencing and digitization processes. All the derived thematic maps such as lineament, geology, soil, slope, NDVI and LULC were subjected to multiple influencing factors (MIF) procedures for estimation of weight. Composite soil erosion potential was developed by the assimilation of reclassified influencing factors and sub-level classes using weighted linear overlay technique. Erosion occurrence data were used to validate the soil erosion potential (SEP) map. The developed SEP classified the study area into three zones; low (30.79%), moderate (44.80%) and high (24.41%). The SEP map exhibits 75% accuracy when referenced with erosion occurrence field data whereby 75.59% of the study area fall within low and moderate soil erosion potentials with tendencies for sheet and reel erosion respectively. Such that high soil erosion potential constituting 24.41% is susceptible to gully erosion largely within built-up areas with threat to humans. Thus, the GIS-model employed in this study was effective in delineating erosion potential zones so as to improving preparedness and early warning for adverse events needed to formulate erosion prevention and management strategy.
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