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Samuel, Adelabu
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Trend Analysis of Climate Variability and Land-Use Dynamics in a Data-Scarce Region of Southwest Nigeria Using Remote Sensing and Meteorological Data Adenrele, Adeniyi Sunday; Samuel, Adelabu; Olusegun, Ekanade; Sunday, Durowoju Olufemi; Mutiso, Jackson Colbert; Anthony, Kola-Olusanya
Geosfera Indonesia Vol. 11 No. 1 (2026): Geosfera Indonesia
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v11i1.60001

Abstract

This study investigates long-term climate variability and land-use dynamics in the Ife Region of Southwest Nigeria using an integrated, multi-source geospatial framework spanning 1984-2024, addressing persistent data limitations in the region. Meteorological data, including daily and monthly rainfall and temperature records, were obtained from the Climate Hazards Group InfraRed Precipitation (CHIRPS) and ERA5-Land datasets, respectively and complemented by satellite-derived variables NDVI, land surface temperature (LST), and land-use/land-cover (LULC) acquired from Landsat (TM, ETM+, OLI/TIRS) imagery of 30m resolution. Accuracy assessments were conducted for all classified years to ensure the reliability of the results. Results show a mean air temperature rise of about 1.24°C over the study period, equivalent to a trend of +0.031°C per year, alongside a progressive increase in annual rainfall at +7.28mm per year. LST intensified significantly, increasing by 3.6 - 5.2°C in urban areas and 2.1 - 3.4°C in rural areas. Vegetation condition weakened markedly, with peak-season NDVI decreasing from 0.68 in 1984 to 0.42 in 2024, indicating heightened vegetation stress. LULC analysis revealed extensive spatial transformation: Undisturbed Forest declined by 540.05km² (-56.95%), while Farmland and Built-up Areas expanded by 253.87 km² (+95.47%) and 124.23 km² (+38.40%), respectively. Classification reliability remained consistently strong, with Overall Accuracy values ranging from 93.5% to 96.1% and Kappa coefficients of 0.90–0.95. The regression model explains 86.9% of LST variability in the Ife Region (R² = 0.869; F(6, 45) = 50.05, p < 0.001), with temperature (β = 0.789), Built-up Areas (β = 0.321), and forest cover (Undisturbed: β = –0.266; Disturbed: β = 0.198) as main drivers. Urbanisation and forest loss increase warming, while intact forests and rainfall (β = –0.178) provide cooling, highlighting the combined effects of land-cover and climatic factors on surface temperatures. These interacting shifts heighten ecological stress, influence hydrological stability, reduce agricultural resilience, and amplify urban heat conditions.