Urbanization in sub-Saharan African cities is altering the land surface and local climate conditions. However, the empirical data on the spatiotemporal patterns of land surface temperature (LST) along the urban–rural gradient at the local administrative level is scarce. Therefore, this study assessed the impact of land use/land cover (LULC) change on the LST dynamics in Lagos Mainland, Nigeria, a rapidly urbanizing area within Africa’s most rapidly expanding megacity, between 2015 and 2025 using a combination of GIS and remote-sensing techniques. Multitemporal Landsat 8 OLI/TIRS data (30 m resolution) acquired during the dry season months were employed for this analysis. The data were classified using a supervised classification technique and the maximum likelihood classifier to produce the LULC maps for 2015, 2020, and 2025. LST was obtained in three steps: conversion to spectral radiance, computation of brightness temperature, and emissivity correction using NDVI-based approach. A confusion matrix was used for accuracy assessment and an overall classification accuracy of 87.5% (κ = 0.84) was achieved. A significant LULC change occurred, i.e., 71.1% decline in the vegetation area (from 1065 to 308 ha) and 748.5% rise in the bare area (from 97 to 823 ha) from 2015 to 2025 and built-up area increase (from 867 to 1067 ha). The spatiotemporal variation in LST was found to be prominent as the mean surface temperature was increased from 27.61 °C (2020) to 41.22 °C (2025). Furthermore, the results of the spatial overlay analysis and bivariate correlation analysis show that there are strong positive correlation values between LST and built-up area (r > 0.80) and significant negative correlation values between LST and vegetation area (r < -0.70), thereby showing that green spaces have potential in mitigating thermal conditions. Thus, the results of this study give an empirical insight into the association between LST and land use and land cover types as evidence of the thermal impacts of urbanization at local administrative level and therefore calls for the need to consider LULC planning strategies to mitigate UHI effects. The study also shows that the use of high resolution remote sensing data is effective in the application of SDGs in tropical developing cities with limited data, and also provides baseline data for policy implications on UHI in rapidly urbanising African cities.