Surveying & Geoinformatics

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Surveying & Geoinformatics

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    Flood Inundation Mapping of Gbaganu Area Minna, Niger State
    (School of Environmental Technology, Federal University of Technology, Minna, Niger State, 2021-05-05) Adesina, E.A., Saka, T.T., Adewuyi A.I., Ayoade, S.A., and Ayndeji, M.A.
    Flooding in recent times has become a critically problematic phenomenon of spatio-temporal order and considerably high frequency of occurrence worldwide. Gbeganu area of Minna covering an area of 16.389 hectares within Niger State. Nigeria has witnessed and is still witnessing multivariate cases of flooding, which peak in the rainy season (April-October) of every year, resulting in loss of life and economic valuables/properties. To curb this menace, an integrated solution of drainage morphometric parameters with remote sensing and geographical information system capacity is thus herein presented using the downloaded Shuttle Radar Topography Mission (SRTM) of 1-arc second (30 m resolution) which covers nearly the entire Niger State and the DEM of the study area was extracted and digital elevation model (DEM) generated from topographical point data (position and elevation of points within the area) taken with Differential Global Positioning System receivers and the satellite image of the study area to delineate watershed, contributing area, flow direction and flow path/channel. The Height Above the Nearest Drainage (HAND) tool was used on the ArcGIS software for analyses. The study produced a map depicting regions within the study area: regions that are highly susceptible to flooding. The morphometric analysis of flood inundation hazard in the area watershed shows that the risk to buildings will be more serious shortly, meanwhile, the implementation of flood countermeasures and the identification of priority areas for flood risk reduction using the flood inundation map will also help to reduce the flood impacts within the study area.
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    Analysis of Telecommunication Service Mast Distribution in Minna, Niger State Using Geospatial Technique
    (National Association of Surveying and Geoinformatics Lecturers (NASGL), 2019-02-07) Adesina, E.A., Uloko, U.S, Olaniyi, M.K., Animashahaun, A., and Abdulkareem, S.
    Since the embrace of telecommunication in Nigeria, the number of subscribers has tremendously increased and the dependence on telecommunication has grown cutting across all professions to all man’s day-to-day activities. This high rate of growth has led to high pressure on the telecommunication facilities, leading to poor network coverage. The increasing number of subscribers and the high dependence of everyone on telecommunication for man’s day to day activities require that research to made into investigating ways to totally eliminate or minimize poor network coverage within the study area. Over the years researchers from different fields have looked into this problem with attempts to help solve this problem, and they most times tend to get stuck with topographic problems. This research tends to look into the analysis of telecommunication mast distribution using geospatial techniques in Minna Metropolis. The aim of this research is to analyse the spatial location (X, Y, and Z) of the telecommunication masts in Minna Metropolis in view of enhancing the performance and efficiency of telecommunication services in the metropolis. The parameters of the mass were acquired from the telecommunication company and a street guide map of the metropolis updated with the mast’s locations was used to locate the masts and trigonometric levelling of inaccessible points was used in getting the height of the mast. The geospatial analysis used was view shed analysis incorporating buffer analysis; this was overlaid on the street guide map and a Digital Elevation Model (DEM). The view shed analysis was used to access the effect on topography on the network coverage while the buffer analysis was used to depict the range of network coverage. The results showed that the distribution pattern is based on population density and the concentration is on commercial centers and areas where income per head is high. It is also revealed that the masts are well distributed for good 2G coverage, but poor network coverage is still seen due to topographic obstruction. The study also reveals that the facilities were poorly distributed for good 3G coverage at the fringes of the metropolis. It was discovered that topography has effect on the network coverage, as topographic features tends to obstruct the line of sight signals from the mast. High peak produces better visibility and signal reception than on lowlands in the line of sight and view shed analysis. It was also discovered that in places where masts are well distributed and poor network is still seeing, increasing the height of the mast could actually help in solving the problem. The work recommends that masts be placed at high peaks where the line of sight would not be obstructed. Also, LIDAR and UAV generated digital elevation models can be used for the analysis to obtain better accuracy. The research recommends that this can serve as forehand information for business men regarding where to establish businesses related to telecommunication and location.
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    GIS-based soil loss estimation using revised universal soil loss equation
    (7th Intercontinental Geoinformation Days (IGD)-Peshawar, Pakistan, 2023-11-19) Ekundayo Adesina, Oluibukun Ajayi, Joseph Odumosu, Abel Illah
    Soil loss estimation plays a vital role in the management and conservation of land and water resources, offering vital insights for watershed-level development in various regions. This study focuses on the development of a soil loss model for the Bosso Local Government Area in Minna, Nigeria, utilizing the Revised Universal Soil Loss Equation (RUSLE). Integration of Landsat images, Digital Elevation Models (DEM), rainfall and precipitation records, and soil erodibility factors were employed to estimate the average annual soil erosion within the study area. The individual parameters of the RUSLE model were integrated into the ArcGIS environment using the raster calculator in the Arc toolbox. The results reveal that an alarming 6672.83 tonnes per hectare per year of soil are lost annually in the study area. This rate of soil erosion raises concerns about the sustainability of agricultural practices in the study area. The findings underscore a critical absence of conservation practices or plans to combat and mitigate soil erosion in the region. In light of these findings, it is imperative that local government authorities, in collaboration with various ministries, take immediate action to promote and enforce conservation measures aimed at combating soil erosion within the area
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    Land Cover Classification: Comparison between Fuzzy and Boolean Classifier
    (FIG Working Week 2016 Recovery from Disaster Christchurch, New Zealand, May 2–6, 2016, 2016-05-06) Abdullahi Ahmed KUTA, Oluibukun Gbenga AJAYI, Ekundayo Abayomi ADESINA, Zitta NANPON, Hassan .A. SAMAILA-IJA
    Production of Land Use/Land cover maps is very important for environmental monitoring and development. Image classification using either hard/or soft classifiers is crucial in the production of these maps. While fuzzy classification is suitable for modelling vagueness due to mixed pixels in the land cover, Boolean, on the other hand, is suitable for modelling land cover with well-defined boundaries. The analyst’s choice of image classifier is a very important decision in image classification, as this determines the classification output. Using Landsat5 TM of 1984, Landsat 4 TM of 1992 and Landsat7 ETM+ of 2000 satellite images, this research looks at the comparison between soft (Fuzzy) and hard (Boolean) classifiers. The Landsat ETM+2000 of a 15m spatial resolution was resampled to a 30m pixel size so that the three images would be of the same pixel size to effectively carry out pixel-to-pixel analysis. Due to the nature of the landscape and bearing in mind that land cover responds differently to various Landsat spectral bands, three band combinations (image bands 2, 3, and 4) were considered for the classification. The images were classified into four (4) different land spectral classes by employing the fuzzy membership function and maximum likelihood classification tools in Idrisi Taiga 16 software. The results obtained show that the spatial distribution of the modelled land cover classes for both Fuzzy and Boolean is the same, which buttresses the performance level of both models. The major difference between the two models lies in the output; while fuzzy shows a subtle representation according to the degree of membership function of each land cover class, the Boolean, on the other hand, represents the land cover types with a well-defined boundary. Also, the summation of the fuzzy land cover areas is not equal to the size of the study; 108% in 1984, 107% in both 1992 and 2000, are unlike the Boolean with 100%.
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    Dynamic Road Segmentation of Part of Bosso Local Government Area, Niger State
    (American Journal of Geographic Information System 2015, 2015) Oluibukun G. Ajayi, Joseph O. Odumosu, Hassan A. Samaila-Ija, Nanpon Zitta, Ekundayo A. Adesina, Olaniyi J. Olanrewaju
    Dynamic road segmentation (DRS) data model finds maximum application in GIS Transportation (GIS-T) studies and analysis, serving as a data model that splits linear features into a new set of segments wherever its attributes change. An attempt has been made by this research to carry out the Dynamic road segmentation of part of the Bosso Local Government Area of Minna using an IKONOS image of 1-m Pan-sharpened spatial resolution and other field survey acquired data. Geometric data was acquired using Handheld GPS receivers while the attribute data was acquired via the social survey approach(administration of questionnaires, direct observations, and on-site interviews). A Geo-database was designed and created within the ArcGIS 10.0 software environment. Analysis and queries were also performed to solve some pertinent issues concerning the route segments and to highlight the closest infrastructural facility in case of emergencies. The result highlighted the present road pavement condition of the considered road segments, adjacent land use, traffic congestion rate, notable crime spots, and accident hotspots. It also suggested that the building up of traffic congestion along the Kpakungun roundabout axis is due to the road width (8m), high traffic volume, and the dilapidating state of the road’s pavement.
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    Modelling Surface Runoff and Mapping Flood Vulnerability of Lagos State from Digital Elevation Model
    (FIG Congress 2014 Engaging the Challenges – Enhancing the Relevance Kuala Lumpur, Malaysia 16-21 June 2014, 2014-06) Olayemi Joseph ODUMOSU, Oluibukun Gbenga AJAYI and Ekundayo ADESINA
    Flooding in recent times has become a critically problematic phenomenon of spatio-temporal order and considerably high frequency of occurrence all over the world, and most especially in coastal nations/states. Lagos State, one of the nine (9) Coastal States of Nigeria, has witnessed and is still witnessing multivariate cases of flooding which attains its peak in the rainy seasons (April-October) of every year resulting in loss of life and economic valuables/properties. To curb this menace, an integrated solution (combination of empirical hydrological models with remote sensing and GIS capacity) is thus presented herein using a downloaded Digital Elevation Model of the study area to delineate watersheds, flow direction, contributing areas, and flow path/Channel. Also, surface runoff was simulated for an eight-hour homogeneous rainfall, and the resulting gauge readings from eleven (11) fictitious gauge stations distributed across the state were obtained. The study was able to produce a map categorising Lagos state into three (3) zones based on their vulnerability to flood. The Quantum GIS software was used for the analysis and simulation.
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    AN EVALUATION OF GEOMETRIC DATA ACQUISITION USING LANDSAT IMAGERY
    (CASLE – Abuja 2016 Conference Papers., 2016) Oluibukun .G. Ajayi, Yusuf .D. Opaluwa, Quadri .A. Adejare, Joseph. O. Odumosu, Nanpon Zitta and Ekundayo .A. Adesina
    The implementation of appropriate digital image processing method is crucial for deriving urban land cover maps of acceptable accuracy and cost. This study examines the effect of acquiring images in various spectral regions (bands), the impact of some image processing techniques on the combination of the different bands and the acceptable mode in which the features of the image could be classified using unsupervised classification (clustering) and supervised classification based on four different hard classifiers. Four different filter types were experimented on the colour composite images before classifying the images into different distinct land spectral classes. The Integrated Land and Water Information System (ILWIS) software was used to classify LandSAT 7 image of 2001, part 189r053, zone 32, bands 1 (Blue), 2 (Green), 3 (Red), 4 (Near infrared), 5 and 7 (Middle infrared) wavelength. From the study, it was observed that AVG 3x3 filter type is the most preferred. Colour composite of bands 5, 4, 3 in the RGB planes gave the best representation of the features of the image and that Box classifier, Minimum Distance to Mean Classifier and Maximum Likelihood classifier are excellent classifiers for image supervised classification