Spatio-Temporal Dynamics of Vegetation Response to Climatic Variability in Akinyele Local Government Area, Oyo State, Nigeria
DOI:
https://doi.org/10.33003/fjs-2026-1016-5660Keywords:
Vegetation dynamics, NDVI, Climatic variability, Land surface temperature, Sentinel-2, Google Earth Engine, NigeriaAbstract
Although vegetation is very sensitive to climatic variability, there is limited evidence on a local scale in many tropical areas. This study has evaluated the spatio-temporal variability of vegetation response to climatic variability in Akinyele Local Government Area, Oyo State, Nigeria using NDVI, Rainfall, LST data of multi-temporal satellite image for the years 2015, 2020 and 2025. Google Earth Engine was used to process the sentinel-2 imagery, CHIRPS rainfall data, and MODIS LST products. NDVI was categorized into 3 classes (sparse, moderate and dense vegetation). The data set consisted of 5,991 sample points with which statistical analyses (Pearson correlation, multiple linear regression, ANOVA) were carried out. Results indicated that from 2015 to 2020 the density of vegetation decreased by 126.45 km² but increased by 158.55 km² until 2025, in accordance with the climatic changes. Mean NDVI decreased from 0.629 in 2015 to 0.611 in 2020, then increased to 0.654 in 2025. LST had a consistently high negative correlation (r = -0.650 to -0.669, p < 0.001) with NDVI, whereas there was a relatively weak positive correlation with rainfall (r = 0.291–0.336). Regression models accounted for 43%–45% of the variability in NDVI, with LST being the most significant predictor (p < 0.001). The results provide a basis for understanding how temperature is the dominant climatic factor controlling vegetation in the study area, and its implications for land use planning, climate change adaptation, sustainable agriculture, and urban green infrastructure in the urbanising landscapes of Nigeria.
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