Department of Geomatics

Rapid urbanization and land-use modification have intensified surface temperatures in many developing cities, including Benin City, Nigeria. This study assessed the spatio-temporal variations in Land Surface Temperature (LST) and Urban Heat Island (UHI) intensity in Benin City from 2014 to 2024, and examined the relationship between land-cover changes and surface thermal patterns using Remote Sensing and Geographic Information System (GIS) techniques. Landsat satellite imagery was processed to derive LST, Normalized Difference Vegetation Index (NDVI), and Land-Use/Land-Cover (LULC) maps. Change detection analysis, raster differencing, and statistical evaluation were used to quantify temperature variations, land-cover transitions, and UHI development. Results showed a noticeable increase in surface temperature over the study period, particularly within built-up areas where expansion and conversion of vegetated land were observed. Vegetation loss weakened natural cooling functions, while the growth of impervious surfaces contributed to higher thermal retention. Correlation analysis further confirmed a strong negative relationship between NDVI and LST, indicating that areas with dense vegetation experienced significantly lower temperatures. UHI hotspots intensified within densely urbanized zones, reflecting the impact of urban growth on thermal conditions. The study concludes that urbanization in Benin City is a major driver of increasing surface temperature and strengthening UHI effects. It emphasizes the need for sustainable urban planning strategies, including urban greening, heat-responsive development, and environmental regulation, to enhance thermal comfort and climate resilience. Findings provide valuable geospatial insight for policymakers, urban planners, and environmental stakeholders in promoting climate-adaptive development within the city

Water distribution plays a vital role in ensuring the sustainability and functionality of institutional environments. The University of Benin (UNIBEN), Ugbowo Campus, has experienced increasing water supply challenges over the years due to population growth, uneven distribution, leakages, and aging infrastructure. This project focused on the application of Geographic Information System (GIS) technology to analyze and manage the existing water distribution network of the campus with the aim of improving efficiency, monitoring, and future planning. Both spatial and non-spatial data were obtained through field surveys, and records from the UNIBEN Works Department. The data were processed and integrated into a geospatial database using ArcGIS 10.8 and Google Earth. The study involved the generation of a Digital Elevation Model (DEM) and 3D terrain analysis to determine the relationship between topography and water flow. Population projection and water demand analysis were carried out using the compound growth rate method and standard per capita consumption rate of 150 litres per person per day. The results showed that the campus terrain ranges from 74 to 121 metres above mean sea level, with the UNIBEN Water Scheme strategically located at the highest elevation to support a gravity-fed distribution system. The projected population increased from 40,320 in 2015 to 76,576 in 2040, representing an 89.9% rise over the 25-year design period. Consequently, the maximum daily water demand was estimated to increase from approximately 10.89 million litres in 2015 to 20.68 million litres in 2040. The pipeline network mapping revealed a well-structured system composed mainly of Asbestos Cement (AC) and PVC pipes, though aging sections require replacement. iv In conclusion, the integration of GIS technology proved to be an effective tool for analyzing, managing, and visualizing water distribution systems. The study provides a comprehensive spatial database that can assist the University in maintenance planning, leak detection, infrastructure upgrading, and sustainable water management. It also demonstrates that GIS-based approaches can significantly improve decision-making in institutional water supply systems and serve as a model for similar environments across Nigeria.

Accurate topographic mapping is vital for effective land-use planning, infrastructure development, and environmental monitoring. The integration of advanced remote sensing techniques, particularly the use of Unmanned Aerial Vehicles (UAVs), is highly advantageous for creating efficient and precise terrain models. The importance of high-resolution topographic data cannot be overstated, as it is integral to engineering applications and geospatial analysis. This study aims to produce a detailed topographic map of the University of Benin's Ugbowo Campus, located along the Benin-Lagos Expressway in Benin City, Nigeria, utilizing the DJI Phantom 4 RTK drone. The methodology employed key topographic parameters, including elevation, slope, aspect, and terrain variation, to create a high-accuracy Digital Elevation Model (DEM). A UAV was operated at an altitude of 120 meters in a 3D flight mode, capturing high-resolution aerial imagery. To ensure precise geo-referencing of the orthophoto, Real-time Kinematic (RTK) GPS technology was utilized with an RTK-enabled drone, thus eliminating the need for Ground Control Points (GCPs). The acquired imagery was then processed to produce an orthophoto, which served as the basis for deriving the DEM, and contour lines were extracted at 5-meter intervals to illustrate elevation variations. The accuracy of the model was assessed through a positional accuracy analysis, revealing that the generated topographic data achieved a remarkable precision of less than 5 cm. This outcome underscores the high accuracy of UAV-based mapping techniques. The resulting topographic map provides a comprehensive representation of the terrain, facilitating improved decision- making in urban planning, construction, and geospatial analysis. In conclusion, this research showcases the effectiveness of UAV photogrammetry, particularly through the integration of RTK technology, in producing precise topographic maps. It highlights the promise of UAV-based surveys as a cost-effective and efficient alternative to traditional surveying methods, especially in challenging or inaccessible terrain. By achieving exceptional positional accuracy, these techniques not only enhance the quality of the collected data but also significantly contribute to improved decision-making across various domains, including urban planning and construction.

This study investigates the influence of satellite constellation configurations on the positional accuracy of post-processed static GNSS data at the University of Benin, Ugbowo Campus. Static observations were collected at five known control points using a Tersus David30 receiver. Data was processed in Tersus Geomatics Office across seven constellation setups: GPS-only, GLONASS-only, BEIDOU-only, and their combinations. A detailed epoch-based analysis was also conducted at one control point using RTKLIB. Accuracy was assessed using coordinate residuals (∆E, ∆N, ∆H), RMSE, standard deviation, CEP, and 2DRMS, supplemented by classical
and robust statistics and time-series analysis. Results demonstrated that GPS-based solutions consistently delivered superior performance. The GPS+BEIDOU combination achieved the best accuracy (2DRMS = 0.160 m, CEP = 0.067 m), closely followed by GPS-only. In contrast, BEIDOU-only yielded the poorest results (2DRMS = 0.587 m), while GLONASS-only was notably weak and unstable. RTKLIB processing confirmed that multi-constellation setups, particularly GPS+GLONASS+BEIDOU, produced highly precise solutions with sub-centimeter standard deviations. Conversely, the GLONASS-only solution exhibited severe instability, with significant errors and outliers. Time-series analysis revealed that stable constellations maintained narrow error bands, while error spikes in other configurations corresponded directly to drops in satellite visibility

Flooding is a recurring environmental hazard that continues to pose significant challenges to urban development, particularly in rapidly growing cities of developing countries like Nigeria. This study investigates the causes, extent, and possible mitigation measures for flooding along Edaiken Primary School Road and its environs in Benin City, with the aim of improving stormwater management and promoting sustainable urban resilience. The researchevaluates the efficiency of existing drainage infrastructure, identifies flood-prone zones, and designs an appropriate drainage system to mitigate runoff accumulation. A combination of field observations, hydrological data collection, and GIS-based spatial analysis was employed to assess catchment characteristics and flow patterns. The drainage catchment was delineated into five sub-catchments (SC1–SC5), each with distinct topographic and hydrological properties. Results from the analysis revealed that sub- catchments SC3 and SC4 contribute the largest volumes of runoff due to their lower elevation and higher flow accumulation potential. The hydrological parameters indicated short times of concentration (0.284–0.583 hours) and high rainfall intensities (137.034–175.972 mm), which are typical of urbanized areas with low infiltration capacity.

Urbanization significantly alters natural landscapes, often leading to vegetation loss and environmental degradation. This study assesses the impact of urban expansion on natural vegetation in Ikpoba-Okha using Landsat satellite imagery. By analyzing multi-temporal remote sensing data, the research examines land cover changes, vegetation decline, and urban growth patterns over time. Image classification techniques, such as Normalized Difference Vegetation Index (NDVI) analysis, are employed to quantify vegetation loss. The findings provide valuable insights into the ecological consequences of urbanization, aiding in sustainable land-use planning and environmental conservation efforts in the region.

Ikpoba Dam serves a singular purpose - the provision of potable water to the populace of Benin City. However, the dam's functionality has been adversely affected by acute sedimentation. In response, comprehensive bathymetric surveys were conducted to assess the volume of sediment accumulated during its operational period. This study delves into a thorough investigation
employing a longitudinal profiling technique for short-term mapping of Ikpoba Dam's bottom topography. The primary objectives encompass determining short-term variations in the longitudinal profile of the dam's bottom, generating short-term Digital Terrain Models (DTMs) of the dam's bottom topography, and calculating the accumulated sediment volume by everaging Digital Elevation Models (DEMs) differencing.

This project explores the use of finite element analysis (FEA) methods for the Physics Department building's deformation monitoring. For buildings to remain structurally sound and safe, deformation monitoring is essential, especially for those that are subjected to changing loading bearing and climatic conditions over time. A comprehensive approach for modeling and assessing the structural behavior of complex structures, such as buildings, under various conditions is provided by the Finite Element Analysis (FEA) method. Taken into account its geometric, material, and loading properties, FEA is used in this work to model the Physics Department building. The assessment of the building's response to varying loads and environmental conditions involves the evaluation of several deformation parameters, including displacements, strains, stiffness and stresses. The results of this study help in the construction of effective deformation monitoring plans for structures that are similar to the Physics Department building and offer insightful information about the structural integrity of the building. The methodology involves the strategic placement of GNSS receivers, considering topographic features, and environmental factors. The selected GNSS receivers are equipped with advanced capabilities for precise positioning, enabling the monitoring of both static and real-time information. The project also integrates quality assurance measures, such as regular calibration checks, redundancy protocols, and real-time corrections, to ensure the reliability of the collected data. The anticipated outcomes of this project include a comprehensive dataset detailing the deformations observed in the monitored structures area over a period. Furthermore, the research advances finite element analysis (FEA) methods in structural engineering by improving their accuracy and practicality.

Flooding, erosion, and inadequate drainage systems have continued to pose significant
hydrological challenges affecting the durability and performance of road infrastructure in
Benin City. One of the most impacted corridors is Temboga Road, situated within the IkpobaOkha Local Government Area. This study employs Geographic Information Systems (GIS)
and Remote Sensing methods to evaluate the hydrological characteristics of the Temboga
area and develop sustainable solutions for resilient hydraulic infrastructure design and
planning. Digital Elevation Models (DEMs) sourced from the Shuttle Radar Topography
Mission (SRTM/ USGS), combined with high-resolution UAV (Phantom 4) imagery and
differential GNSS observations, were processed within ArcGIS Pro and Global Mapper
environments to delineate watersheds, trace flow accumulation pathways, and identify floodprone zones. The Rational Method was applied to estimate peak runoff, while GIS-based
spatial were used to evaluate drainage and erosion-vulnerable locations. Findings indicate that Temboga Road lies across multiple sub-catchments (eight in total)
within the Ikpoba River basin characterized by low-lying topography, high rainfall intensity
exceeding 2,400mm annually, and sandy-loam soils that are highly susceptible to erosion.
The integration of GIS and hydrological analysis proved instrumental for evidence-based
decision-making, enabling engineers and planners to visualize water flow dynamics, mitigate
flood risks, and design drainage systems that strengthen the resilience and sustainability of
road infrastructures. Ultimately, this research demonstrates the value of spatial intelligence in
transforming traditional hydrological assessments into proactive tools for sustainable
infrastructural development along Temboga Road, Benin City.

Flooding brought on by excessive rainfall is one of the frequently occurring and widely reported disasters affecting human existence. The purpose of this study is to create flood risk maps of Ikpoba Okha which can be used for predicting the level of vulnerability due to rapid urban development taking place in recent times. The procedure to achieve this involved using the method of Analytical Hierarchy Process (AHP) in a Geographic Information System (GIS) environment. Among the fundamental datasets requirements for the project were: cloud-free high-resolution satellite images, SRTM DEM data, FAO soil data, rainfall data, etc. Maps of flood-enhancing elements, such as
flood risk vulnerability mapping, were created in Geographic Information Systems using the same scale of 1: 200,000 and geographic coordinate system (WGS 1984 UTM zone 31N). This multiparametric technique includes rainfall distribution, elevation and slope, drainage network and density, land use/land cover, and soil type, among other flood determinants. All the output raster maps
were first ranked using the "Weighted Linear Combination" method with a grid cell size of 0.0028 mm before being sent for Multi-Criteria Analysis (MCA). The computation of the consistency ratio at an acceptable level of 0.055 further confirmed the model's validity. Additionally, the research found topography and rainfall as the most significant factors contributing to floods in Benin City.