VEGETATION

ASSESSMENT OF LAND USE AND VEGETATION COVER CHANGES OF A PUBLIC INSTITUTIONAL PREMISE IN BENIN CITY, EDO STATE

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Abstract
Land use and land cover changes within tertiary educational institutions significantly impact environmental sustainability, biodiversity, and ecological health. This study examined spatiotemporal variations in land use/land cover (LULC) and vegetation dynamics of the University of Benin, Ekehuan Campus, Benin City, Edo State, Nigeria, over a 50-year period from 1975 to 2025. Landsat satellite imagery from the years 1975, 1985, 1995, 2005, 2015, and 2025 respectively was processed using Google Earth Engine (GEE) and ArcGIS platforms, with classifications categorized into dense vegetation, sparse vegetation, agricultural land, built-up areas, and bare soil. Supervised Maximum Likelihood Classification was employed for LULC analysis, while the Normalized Difference Vegetation Index (NDVI) was computed to assess vegetation health. Field surveys documented remaining tree species in the study area. Results revealed catastrophic vegetation decline from 0.841334 km² (97.34%) in 1975 to complete elimination (0%) by 2015-2025. Built-up areas increased dramatically from 0% in 1975 to 0.671581 km² (77.70%) by 2025. Agricultural land fluctuated from 0% to 36.49% (2015) before declining to 16.06% in 2025. Bare soil emerged at 6.24% in 2025, indicating land degradation. NDVI values ranged from - 0.077 to 0.400 across the study period, with maximum values declining from 0.400507 in 2005 to 0.26453 in 2025. Field surveys documented only 16 tree species in 2025, representing severe biodiversity loss compared to historical diversity. These findings revealed complete landscape transformation from a natural ecosystem to an urbanized environment, resulting in total habitat destruction, loss of ecosystem services, hydrological disruption, and biodiversity collapse. It is recommended that campus planning incorporate mandatory green infrastructure, sustainable urban drainage systems, and stringent land-use controls to mitigate environmental degradation and promote sustainability.
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co-supervisor

A STUDY OF THE INTEGRATION OF VEGETATION IN RESIDENTIAL BUILDINGS IN BENIN CITY, EDO STATE

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Abstract
The earliest vertical gardens extend back 2000 years to the Mediterranean region, and ornamental roof gardens were first created by the civilizations that inhabited the basins of the Tigris and Euphrates rivers (the most famous examples of which were the Hanging Gardens of Babylon in the seventh and eight centuries B. C.). Northern European regions, such as Norway's sod roofs or the Mediterranean basin's climbing plants for shading vertical surfaces, have a number of examples of green roofs and façades dating to the 18th and 19th centuries. To support sustainable construction practises, modern building envelopes also contain cutting-edge materials and other technologies.
Supervisor(s)
co-supervisor

SPATIO-TEMPORAL CHANGE DETECTION ANALYSIS OF VEGETATION COVER IN EDO STATE

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The degradation of vegetated lands due to modernization, agricultural expansion, and climate change has become a growing environmental concern in Edo State, Nigeria. Vegetation plays a critical role in sustaining biodiversity, regulating local climate, reducing soil erosion, and supporting livelihoods through agriculture and forest resources. However, rapid population growth, increasing demand for land, and infrastructural development have intensified pressure on natural vegetation across the state. This study aims to map and monitor the spatio-temporal dynamics of vegetated lands in Edo State using satellite remote sensing data within the Google Earth Engine (GEE) platform. Multi-temporal satellite imagery of Edo State was acquired and preprocessed using Moderate Resolution Imaging Spectroradiometer (MODIS) data as the primary source. Vegetation indices, particularly the Normalized Difference Vegetation Index (NDVI), were computed to classify and map vegetated areas and to evaluate vegetation health and density over time. Time-series analysis and pixel-based classification techniques were applied to assess vegetation patterns and to detect changes in vegetation cover between 2015, 2020, and 2025. The NDVI-derived vegetation classes were categorized into dense vegetation, sparse vegetation, and non-vegetated or built-up surfaces to enable clearer interpretation of vegetation transformation.
Supervisor(s)
co-supervisor