Determination of Land Use, Drainage, and Elevation Map of Lower River Ogun, South-Western, Nigeria, Using GIS and Remote Sensing

470 Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 470-474 p ISSN: 2635-3342; e ISSN: 2635-3350 Original Research Article Determination of Land Use, Drainage, and Elevation Map of Lower River Ogun, SouthWestern, Nigeria, Using GIS and Remote Sensing Adeyokunnu, A.T. Department of Civil Engineering, Ajayi Crowther University, Oyo, Oyo State, Nigeria. [email protected] http://doi.org/10.5281/zenodo.18061554 ARTICLE INFORMATION ABSTRACT Article history: Received 10 Oct. 2025 Revised 11 Nov. 2025 Accepted 12 Nov. 2025 Available online 30 Dec. 2025 This study utilizes Geographic Information System (GIS) and remote sensing techniques to analyze land cover and land use patterns in the Lower River Ogun basin. The primary objectives were to generate land use and elevation maps using ArcGIS 10.3 and Landsat images from 1998, 2003, 2008, 2013 and 2018. The methodology involved georeferencing, overlaying, and classifying the images into five (5) distinct land use and land cover categories. The results indicate that population growth and human development significantly impact land use pattern in Abeokuta. The analysis revealed notable changes in land use dynamics, with vegetation exhibiting the highest gain and loss (24.73 km2), followed by rock (17.53km2), and settlement (16.56km2). Conversely, the bare surface and water body experienced net changes of 2.50 km2 and 1.47 km2, respectively. The elevation map shows a range of 5 – 197 meters above sea level. The study concludes that the land use and land cover of the Lower River Ogun basin have undergone significant changes, with a 43.83% increase in settlement and a 17.10% reduction in water bodies. These findings can help to identify areas prone to flooding and inform flood risk management strategies. © 2025 RJEES. All rights reserved. Keywords: Land use Elevation map Lower River Ogun Remote sensing Geographical Information System 1. INTRODUCTION Human activities such as urbanization are increasing daily due to steady population growth in urban areas. This rapid urbanization has led to the misuse of land, posing a significant threat to the environment. Geographic Information System (GIS) technology is designed to visualize, store, and analyse spatial information about locations, topography, and other environmental features (Alaeddine, 2018). According to Adewale and Liman (2017), GIS programs are capable of storing and managing data in a relational database, enabling dynamic linking between environmental data and their map representations. This linkage between map and database makes GIS an ideal and strong tool for environmental data visualization. Water demand of any community includes: sanitation, drinking, manufacturing, construction, leisure and agriculture. 471 A.T. Adeyokunnu / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 470-474 Integrated water resources management activities include: planning, development, distribution, and management of hydrological features for the optimum use of water resources. Integrated water resources management is an approach that seeks to supply water in the right quantity, quality and allocation of water on a equitable basis to satisfy all uses and demands (Wilson, 2016). GIS is useful to store and manage hydrological data to generating flood inundating and hazard maps. This will be useful in flood risk management (Minya et al., 2008). Most hydrological processes are time dependent. Spatially referenced time-series data are frequently encountered in simulating hydrological events. Therefore, it is important to have an efficient data structure and data management system to handle spatially-referenced time series data. Data structures designed can either be embedded in or connected to a GIS map to manage and analyse the spatially-referenced time series data efficiently and effectively (Olaniyan et al., 2015). Wilson (2016) reported that the environmental agencies have invested substantially in collecting hydrometric and topological data using various techniques. This data is used for a wide range of purposes such as flood risk mapping, catchment flood management plans, shoreline management plans, and integrated coastal zone management using GIS. These results provide essential information for day-to-day asset management and long-term flood risk management. Empirical studies have been carried out on the nature of land use dynamics in Nigeria and other countries Njungbwen et al. (2019) evaluated the land use charges and impact on the Uyo urban settlement, Nigeria, between 1964 and 2004. The result showed that agricultural land constantly dropped in land area, whereas the residential, industrial, institutional and transportation users recorded increases in spatial extent. The study revealed that the rate of loss of agricultural land stood at 0.33 and 4.26 percent between 1969 and 1987, 2001 and 2004, respectively. Land cover/use change information is a very important and useful source for planners in land use studies (Wondrade et al., 2018). One of the relatively inexpensive methods of dealing with land cover changes is the use of remotely sensed data with the invention of remote sensing and GIS techniques. Land mapping is a useful and detailed way to improve the selection of areas designed for agricultural, urban, and industrial purposes (Rawat and Kumar, 2015). 2. MATERIALS AND METHODS 2.1. Brief Description of the Study Area This research is intended for the lower River Ogun, south-western Nigeria, located within Ogun state. It is a waterway in Nigeria that discharges into the Lagos lagoon. The river rises in Oyo state near Shaki and flows through Ogun state into Lagos state (Wilson, 2016). It lies between longitude 2o28′ 33" and 3o 48′ 08" Easthing and Latitude 6o 37′ 10" and 9o26′ 39" Northing with a catchment area of about 23,000 km2. Ogun River takes its source from Igaran hills at an elevation of about 530 m above mean sea level and flows directly southwards over a distance of about 480 km before it discharges into Lagos lagoon (Olaniyan et al., 2017). Lower River Ogun is a big river cutting across three states with more than twenty (20) tributaries, one of which is Oyan River. Its major tributaries are south of the Abeokuta area (Olusola, 2020). River Onigbongbo and Ewekoro, which lies North of Abeokuta that flows southward into Oyan River, which supplies water to Abeokuta and its environment (Olaniyan et al., 2017). 2.2. Arc GIS Mapping This study utilized ArcGIS Mapping to investigate the impact of urbanization in Abeokuta, Ogun State on the Lower River Ogun basin. Landsat Images 7 and 8 acquired in 1998, 2003, 2008, 2013 and 2018 were employed to analyze the effect of urbanization on the river basin. The images were overlaid by retrieving the paths and rows of the area coordinates on the earth survey maps of Abeokuta. Both Digital Elevation Model and the Landsat Imagery were acquired from Google Earth Map. The imagery corresponds to Landsat Enhanced Thematic Mapper (LETM) and Operational Land Imager (OLI) data, whose sensor are on board Landsat 7 and Landsat 8, respectively. The dates of the downloaded Landsat images with corresponding paths and rows were used to determine Land use and land cover variation for Abeokuta and its environment over a particular period of time. 472 A.T. Adeyokunnu / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 470-474 2.3. Land Use Map The input maps required for generating the land-use were obtained from Google Earth of Abeokuta. The map was a scanned contour land-use map of 1998, 2003, 2008, 2013, and 2018. The input maps were imported into ArcGIS environment through a process known as Adding of Data. The Digitized land-use and Google maps were geo-referenced, that is, the map will be given its correct coordinates through the process of geo-referencing within the ArcGIS environment. The extraction of the land use data from the input map will involve other processes such as rectifying, digitizing, laying out and exporting. The land use patterns considered were shrubs, forested, industrial, residential, paved, clayey, loamy, and sandy areas based on the general classification of land use dynamics (2013). Laying out is the act of giving the necessary attributes of a map to our newly produced map (Olaniyan et al., 2017). The land use was classified into five (5) categories as Bare Surface, Water Bodies, Rock Outcrop, Settlement and vegetation in order to study the effect of land use dynamics. 2.4. Digital Elevation Measurement Maps The input data required for generating the Digital Elevation Model (DEM) includes Landsat 7 and 8 images spanning from 1998-2018 with a 5-years interval, covering the Abeokuta region. The elevation data was derived by extracting contour lines from the United States Geological Survey. The DMS acquired for the study areas were redefined using tools in HEC-GEOHMS. The path and row were retrieved by the extraction of Landsat images of Abeokuta. DEM was generated from the contour lines of the catchment by interpolating contour values using GIS. The contour lines were first transformed into point features. The point features were interpolated to produce a spatial variation of elevation within the catchment. The spatially varying elevation will be the required DEM (Adewale and Liman, 2017). 2.5. Land Use and Land Cover Arc GIS was utilized for the analysis of land use and land cover patterns in the study area. The software enabled the calculation of the area covered by each of the land use and land cover categories, which were classified using remote sensing techniques. Furthermore, ArcGIS was employed to perform land change modeling analysis on the classified images, thereby revealing the extent of urbanization in Abeokuta and providing insights into the dynamics of land use changes over time (Alaghmand et al., 2021). Table 1: Landsat TM images of lower river Ogun Date of acquisition Resolution Path/Row Source Landsat 7 (tETM) 18/12/1998 08/12/2003 30m 191/055 191/055 Google Earth Landsat 8 (OLI) 10/02/2008 01/01/2013 04/01/2018 30m 191/055 191/055 191/055 Google Earth (Source: Google Earth United States Geological Survey) 3. Results and Discussion 3.1. Analysis of Land Use and Land Cover Dynamics of Abeokuta The classified Land Use and Land Cover Map of Abeokuta spanning from 1998 to 2018 5-year intervals, are presented. The land use patterns within the Lower River Ogun area in Abeokuta comprise five distinct categories: Bare Surface, Rock Outcrop, Settlement, Vegetation, and Water Bodies. Notably, human activities have been observed to dominate natural processes, with population growth and urban development exerting significant influences on land use patterns in Abeokuta. The rapid pace of development and anthropogenic activities has profoundly impacted the land use dynamics of the area. The flow direction and land use transformation from 1998 to 2018 are quantified in Table 2, providing insights into the changing landscape of Abeokuta over the two decades. The gains and losses in the land use and land cover classification of Abeokuta between 1998 and 2018 are presented in Table 3. A gross gain of one category is always accompanied by a gross loss of another category, so the total gross gain is equivalent to the total gross loss in a landscape. Vegetation has the highest category 473 A.T. Adeyokunnu / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 470-474 in terms of total gross gains and losses with the value 24.73 km2, followed by rock outcrop with net changes of 17.53 km2, since it accounts for gains and losses in the classified land use. While settlement has net change in land use and land cover with the value of 16.56 km2. The bare surface and water body has the net change of 2.50 and 1.47 km2 since it also accounts for point of gains and losses. Thus, the net changes are important to understand the total changes in land use. This is in agreement with previous findings of Alaeddine (2018) and Olaniyan et al. (2017). The Triangulated Irregular Network (TIN) of Abeokuta is presented in Figure 1. It was observed that the hill shade DEM Map makes a difference between a flat, schematic-like Map and a true picture of the landscape. The shaded relief effect is obtained from a digital elevation model, a raster dataset of elevation values. It’s worth nothing that DEMS and hill shades are two separate datasets as DEM contains actual elevation values while hill shade contains brightness values. The TIN Map is used to describe the DEM of Abeokuta. The elevation varies from (5-197) m. Figure 1: Triangulated irregular network (TIN) of Abeokuta Table 2: Land use and land cover classification (1998-2018) Class 1998 2003 2008 2013 2018 Area (km2) Area (%) Area (km2) Area (%) Area (km2) Area (%) Area (km2) Area (%) Area (km2) Area (%) Bare Surface 0.38 0.55 5.95 8.56 4.73 6.82 4.43 6.38 2.46 3.55 Rock Outcrop 7.53 10.84 17.09 24.61 19.13 27.55 24.68 35.54 18.68 26.90 Settlement 28.86 41.56 29.47 42.44 30.06 43.29 25.33 36.48 30.44 43.83 Vegetation 30.79 44.35 15.93 22.93 14.63 21.06 13.95 20.08 16.80 24.19 Water Body 1.87 2.70 1.01 1.45 0.88 1.27 1.05 1.52 1.06 1.52 Total 69.44 100 69.44 100 69.44 100 69.44 100 69.44 100 474 A.T. Adeyokunnu / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 470-474 Table 3: Gains and losses in area covered between 1998 and 2018 Land classes Losses (km2) Gain (km2) Net change (Gains – Losses) km2 Bare Surface -0.21 2.29 2.50 Rock Outcrop -3.34 14.49 17.80 Settlement -7.49 9.07 16.83 Vegetation -19.36 5.37 24.73 Water Body -0.95 0.33 1.47 4. CONCLUSION The Urban Planning and Ogun State Government should regulate and check construction along the bank of the river in Abeokuta. 5. CONFLICT OF INTEREST There is no conflict of interest associated with this work. REFERENCES Alaeddine, E. (2018). Application of Geographic Information System in Soil Classification and Analyses. Palestine Environmental and Natural Resources Research. Alaghmand, S.; Abdullah, R.B.; Abustan, I. and Vosoogh, B. (2021). GIS Based River Flood Hazard Mapping in Urban Area (a case study in Kayu Ara River Basin, Malaysia). International Journal Eng. Technology, 2(6), 488-500. 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