Browsing by Author "Ayo, Babalola"

Now showing 1 - 6 of 6
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    Analytical Land Registration Trends, Difficulties and the way forward in Adamawa state
    (2000-04) Ono, M. N; Ayo, Babalola
    An analysis of land registration data collected for the period of fifteen years (1970 - 1993) was carried out and to analyze the trend patterns. also, efforts are made to identify probable setbacks and difficulties. suggestions are made to ensure appropriate land registration as a way forward
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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
    (published by the faculty of Environmental Sciences, Nasarawa State University Keffi., 2021) Mohammed, O. Idrees; Ayo, Babalola; Dahir, M. Omar; Hussein, A. Ahmadu
    This study assesses the dynamic impact of both human and natural phenomena on Land use Land cover changes between 2014 and 2020 in Ilorin East local government area of Kwara State 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 the supervised maximum likelihood classification (MLC) method. Subsequently, changes in the Land use Land cover that has taken place within the study area was determined using post classification comparison technique. The study revealed that between the years 2014 and 2020, the water body and sparse vegetation decreased by 2% and 3% respectively, whereas the dense vegetation increased by 5%. Also, the rock increased by 3.8%, whereas the barren land and built-up area increased by 5% and 1.4% respectively. Rainfall amount and anthropogenic activities, agricultural practice, increased population, and urbanization are all traced to the pattern of changes detected.
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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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    EVALUATING THE POTENTIAL OF NIKON D3200 AND CANON EOS 7D AMATEUR CAMERAS FOR 3D RECONSTRUCTION
    (Nigerian Institution of Surveyors, 2021-10) Ahmadu, Hussein Adomu; Idrees, Mohammed Oludare; Ayanwale, Victor Opeyemi; Omar, Dahir Muazu; Ayo, Babalola
    The growing use of amateur cameras for several photogrammetric applications such as point determination, three-dimensional reconstruction, measurements and archeological documentation, have ignited studies on the accuracy potential of these categories of cameras. This paper investigates the accuracy potential of Nikon D3200 and Canon EOS 7D amateur cameras for 3D reconstruction of the oldest hostel building in University of Ilorin, Nigeria. Before image collection, a total number of 37 points, 9 control points for image processing and 28 check points for accuracy assessment were strategically marked and coordinated on the building using Sokkia set 520 total Station. Thereafter, multiple overlapping images of the building facade were taken successively with the two cameras in such a way that adjacent pair have end lap of between 80 - 85%. In Agisoft Photoscan, after removing bad images, the photos were aligned. Subsequently, the 3D mesh and textured models wee generated. Corresponding model points of the 28 measured check points were extracted for accuracy determination using the root mean square error (RMSE) analysis. The results showed that both cameras have acceptable point accuracy with the Nikon D3200 producing RMSE of 2.55mm, 3.23mm, 2.51mm and Canon EOS 7D yielded RMSE of 2.77mm, 4.76mm, 2.68mm, in xyz respectively.
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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.
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    Urban land use land cover mapping in tropical savannah using Landsat-8 derived normalized difference vegetation index (NDVI) threshold
    (University of Cape Town, South Africa., 2022-02) Mohammed, Oludare Idrees; Dahir, Muazu Omar; Ayo, Babalola; Hussein, Adomu Ahmadu; Abdulganiyu, Yusuf; Falilat, O. Lawal
    Generation of land use/land cover map at different spatial scales using satellite remote sensing data has been in practice as far back as early 1970s. Since then, research focus has been on the development of classification steps and improving the quality of the resulting maps. In recent times, the demand for detailed high accuracy land-use and land-cover (LULC) data has been on the increase due to the growing complexity of earth processes, while, at the same time, processing step is becoming more complex. This paper explores Landsat 8 derived normalized difference vegetation index (NDVI) threshold for the purpose of simplifying land cover classification process. NDVI images of January, May and December, 2018, representing dry, wet and harmattan seasons were generated. Thereafter, NDVI values corresponding to the location of a set of training data representing the target urban land covers (water, built-up area, soil, grassland and shrub) were extracted. Using the statistics of the extracted values, NDVI threshold for the respective land cover type were determined for the classification process. Finally, the classification accuracy was evaluated using the unbiased matrix coefficient technique which produced overall accuracy of 71.3%, 46.4% and 75.6% at 95% confidence limit for the months of January, May and December of the year review respectively. The result has shown that NDVI threshold is a simple and practical alternative to obtain LULC map at a reasonable time with a few data.