Due to complex and erratic nature of groundwater occurrences in crystalline basement terrains, groundwater development in form of boreholes/wells without the necessary pre-drilling hydrogeological investigations usually results in failure. Therefore, there is the need for adequate characterization of aquifers and delineation of groundwater potential zones in such crystalline basement setting. This study employed the integration of multi-criteria decision analysis (MCDA), remote sensing (RS) and geographical information system (GIS) techniques to delineate groundwater potential zones in crystalline basement terrain of SW-Nigeria and validation of the result with existing borehole/well yield data. The study approach involved integration of nine different thematic layers (geology, rainfall geomorphology, soil, drainage density, lineament density, landuse, slope and drainage proximity) based on weights assignment and normalization with respect to the relative contribution of the different themes to groundwater occurrence using Saaty's analytic hierarchy approach. Following weigh normalization and ranking, the thematic maps were integrated using ArcGIS 10.0 software to generate the overall groundwater potential map for the study area. The result revealed that the study area can be categorized into three different groundwater potential zones: high, medium and low. Greater portion of the study area (84,121.8 km 2) representing about 78 % of the total area, fall within the medium groundwater potential zone which are generally underlain by medium-porphyritic granite, biotite-hornblende granite and granite gneiss bedrock settings. About 18,239.7 km 2 (17 %) fall under high groundwater potential zone which are characterized by weathered/fractured quartzite, quartz-schist, amphibolite schist and phyllite bedrock settings. However, areas of low groundwater potentials constitute only 3 % (3,416.54 km 2) of the total study area and are mostly underlain by migmatite, banded and augen gneiss bedrock settings. Subsequent validation with boreholes/well yield data revealed a good correlation with respect to the observed groundwater potential zonation. Wells/boreholes with yields greater than [150 m 3 /day are generally characteristic of areas with high groundwater potential while those with yields of 75-150 and \75 m 3 /day are typical of areas with medium and low groundwater potentials, respectively. The validation clearly highlights the efficacy of the integrated MCDA, RS and GIS methods employed in this study as useful modern approach for proper groundwater resources evaluation; providing quick prospective guides for groundwater exploration and exploitation in such crystalline basement settings.
Abstract. Vegetation cover over Nigeria has been on the decrease recently, hence the need for adequate monitoring using geo-information technology. This study examined the spatio-temporal variation of vegetation cover over Nigeria for thirty years with a view to developing a strategy for enhancing environmental sustainability. In order to predict the spatial extent of vegetation cover in 2030, the study utilised satellite images from between 1981 and 2010 using the Normalised Difference Vegetation Index (NDVI) coupled with cellular automata and Markov chain techniques in ArcGIS 10.3. The results showed that dense vegetal areas decreased in area from 358,534.
Geospatial analysis of changes in vegetation cover over Nigeria
Schistosomiasis is a parasitic disease and its distribution, in space and time, can be influenced by environmental factors such as rivers, elevation, slope, land surface temperature, land use/cover and rainfall. The aim of this study is to identify the areas with suitable conditions for schistosomiasis transmission on the basis of physical and environmental factors derived from satellite imagery and spatial analysis for Akure North Local Government Area (LGA) of Ondo State. Nigeria. This was done through methodology multicriteria evaluation (MCE) using Saaty’s analytical hierarchy process (AHP). AHP is a multi-criteria decision method that uses hierarchical structures to represent a problem and makes decisions based on priority scales. In this research AHP was used to obtain the mapping weight or importance of each individual schistosomiasis risk factor. For the purpose of identifying areas of schistosomiasis risk, this study focused on temperature, drainage, elevation, rainfall, slope and land use/land cover as the factors controlling schistosomiasis incidence in the study area. It is by reclassifying and overlaying these factors that areas vulnerable to schistosomiasis were identified. The weighted overlay analysis was done after each factor was given the appropriate weight derived through the analytical hierarchical process. The prevalence of urinary schistosomiasis in the study area was also determined by parasitological analysis of urine samples collected through random sampling. The results showed varying risk of schistosomiasis with a larger portion of the area (82%) falling under the high and very high risk category. The study also showed that one community (Oba Ile) had the lowest risk of schistosomiasis while the risk increased in the four remaining communities (Iju, Igoba, Ita Ogbolu and Ogbese). The predictions made by the model correlated strongly with observations from field study. The high risk zones corresponded to known endemic communities. This study revealed that environmental factors can be used in identifying and predicting the transmission of schistosomiasis as well as effective monitoring of disease risk in newly established rural and agricultural communities.
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