Browsing by Author "Ruth, K. Aniyikaye"

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    Detecting Subtle Land Use Land Cover changes at at Small-Scale using Landsat 8 Imagery in Ilorin East Local Government Area, Kwara State, Nigeria
    (Faculty of Environmental Sciences, Nasarawa State University, 2021) Mohammed, O. Idrees; Ayo, Babalola; Dahir, M. Omar; Hussein, A. Ahmadu; Abdulazeez, O. Abdulyekeen; Ruth, K. Aniyikaye; Olatilewa, F. Ojulari
    This study assesses the dynamic impact of both human and natural phenomena on land use land cover (LULC) changes in Ilorin East Local changes Government Area between 2014 of 2020 of Kwara using Landsat 8 Operational Land Imager (OLI) satellite imagery. The images of the respective year were trained and classified into six classes: Built up area, Barren land, dense vegetation, sparse vegetation, rock, and water bodies, using supervised maximum likelihood Classification (MLC) method. Subsequently, changes in Land use Land cover that has taken place within the study area were determined using post classification comparison technique. The study revealed that between years 2014 and 2020, the water body and sparse vegetation decreased 2% and 3% respectively, were as the dense vegetation increased by 5%. Also, the rock decreased by 3.8%, while barren land and built-up area increased by 5% and 1.4%, respectively. Rainfall amount, anthropogenic activities, agricultural practice, increasing population, and urbanization are all traced to the pattern of changes detected.
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    LAND SUITABILITY FOR RICE CROP FARMING IN KWARA STATE USING GIS-BASED MULTI-CRITERIA DECISION ANALYSIS
    (Faculty of Agricultural Sciences and Food, ScCyril and Methodius University in Skopje, Republic of North Macedonia., 2022-03-23) Ayo, Babalola; Mohammed, Oludare Idrees; Ruth, K. Aniyikaye; Hussein, A. Ahmadu; Oyedapo, A. Ipadeola
    This study employs GIS-based multi-criteria decision approach to identify suitable areas for cultivating rice crop in Kwara State, Nigeria, using essential climatic, soil, terrain and environmental variables selected based on FAO framework for land evaluation. Weights indicating the relative importance of each variable was determined using Analytical Hierarchical Process (AHP). The criteria, their weights and constraints were integrated in GIS environment to produce suitability map, classified into five levels of suitability (Very highly suitable, highly suitable, moderately suitable, low suitable and not suitable) using weighted overlay operation. The result indicates that 9.7% (343803.75 ha) of the total land area is unsuitable for cultivating rice while 14.6% (516169.46 ha) is classified as low suitable area. The moderately suitable, highly suitable and very highly suitable classes occupy 30.8% (1091145.20 ha), 40.56% (1436504.55 ha) and 4.4% (154408.94 ha), respectively. Quantitative assessment of the work yields overall accuracy (area under the ROC curve) of 0.97 (97%). Based on the findings of this study, we recommend that the state land use planning agency review zoning mechanism, incorporates grassroots participatory land use planning policy and evaluate suitable land for other essential crops by incorporating GIS in order to sufficiently allocate lands for optimal utilization.