Dahir Omar
@unilorin.edu.ng
Lecturer, Faculty of Environmental Sciences
University of Ilorin
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Mohammed O. Idrees, Sanni A. Olateju, Dahir M. Omar, Ayo Babalola, Hussein A. Ahmadu, and Bahareh Kalantar
Informa UK Limited
Abstract This study assesses and maps accelerated surface runoff and water accumulation hazards in the Ilorin metropolis (Nigeria), using topographic and climatic variables that control accelerated surface runoff and water accumulation. Regarding the accelerated runoff, profile curvature, tangential curvature, drainage density, slope length (L-S) factor, convergence index, catchment shape, land use, and rainfall data were utilized. For the water accumulation process, surface slope, topographic wetness index, drainage density, convergence index, elevation, and altitude above channel were considered together with rainfall and land use. In each case, criteria weights were computed using Multi-Criteria Decision Analysis (MCDA) technique and subsequently integrated into the GIS environment to generate the accelerated surface runoff and inundation hazard maps applying weighted overlay operation. The final map showed that about 35.07 km2 (8%) and approximately 56.55 km2 (14%) of the study area are identified as very high- and highly prone to accelerated surface runoff, respectively. Correspondingly, around 79.89 km2 (18%) and 122.02 km2 (∼28%) belong to the very high and high-water accumulation potential areas, respectively. In summary, it is estimated that about 36% of the water accumulation potential area falls in the densely populated urbanized zones, compared to the accelerated runoff potential detected in undeveloped areas. This implies that there is a higher risk of flooding in the study area than accelerated runoff. However, since the runoff effect occurred mostly in agricultural areas, there is a need for a detailed investigation of this on crop production. Although this study applied a very simple approach, it yielded a high accuracy map (87.5%) which provides useful information for decision-makers to stimulate effective land use planning, alleviate flood occurrence, and reduce soil degradation.
T.O. Lawal, D.M. Omar, M.K. Salami, T. Adewumi, J.A. Sunday, and O. Fawale
IOP Publishing
Abstract Magnetic data of part of Osun State and its Environs, Southwestern Nigeria has been studied with the aim of identifying structures concealing mineral deposits through some enhancement techniques. These techniques are Analytic signal, Euler deconvolution, Center for exploration targeting and porphyry analysis. In this work we were have applied Analytic signal to identify edges and distribution of magnetic sources that are equivalent to concealed mineral deposits, Euler deconvolution was used to identify and estimate depth to various magnetic source geometries using prescribed structural indices of 0.0, 1.0 and 2.0 respectively and lastly, the center for exploration targeting and porphyry analysis was used to obtain magnetic lineaments and porphrytic intrusives that may serve as structures concealing mineral deposits. From this study, we were able to identify several volcanic intrusions which appeared beyond surface exposure and at the same time of Cenozoic era. These intrusions resulted from the high magnetic content which serves as a contributing factor for the presence of positive magnetic anomalies in the area. In conclusion, we have been able use magnetic data of Osun State and its environs to delineate structures concealing mineral deposits.
Mohammed O. Idrees, D Babalola Folaranmi, Dahir M. Omar, Abdul-Ganiyu Yusuf, and Ayo Babalola
IOP Publishing
Abstract This paper presents a comprehensive assessment of the locations, extent and the impact of forest fire in University of Ilorin Teak Plantation using pre- and post-fire Sentinel-2 level 1C products. First, the pre-fire image was classified into three classes: vegetation area, bare soil and water body, using supervised classification (Maximum Likelihood method) to distinguish between vegetation and non-vegetation areas. Then, from the post-fire image, the burn areas were detected and extracted using Normalized Burnt Ratio. With the burn area polygon, impact of the fire on the planted forest was determined by isolating the vegetation class within the classified map so estimating the number of teak trees affected through extrapolation of the burn area and the tree spacing grid of 3m. The classification result shows that vegetation land cover type accounted for about 419.7 ha (66 %) of the total area while bare soil and water body take 204.3 ha (32 %) and 12.9 ha (2 %), respectively. Also, the resulting classified map produced overall classification accuracy of 95 %. Impact assessment result reveals that a total number of 49156 tree stands were affected by the fire within burnt area of 54.8 ha (8.6%). Analysis of the estimation success rate using one of the burn areas as validation site yielded approximation in excess of 3% with 17621 counted and 18222 estimated. Planted forest management and planning has many phases; so, it is necessary to understand the current and future condition of what is being manage. The fire burn map derived from this study will assist the University teak plantation management team update its current management strategy to protect it from continuous exposure to fire. From fire management perspective, the list of planning activities that require future assessments include pruning preferences, replanting, commercial thinning, spacing of planted trees, and perimeter buffering.