<![CDATA[Land cover change is a key factor influencing land surface temperature (LST) dynamics, particularly in coastal urban areas such as Pariaman City. This study aims to: (1) analyze land cover changes in Pariaman City in 2016 and 2023; (2) examine the spatial distribution of LST in both periods; and (3) evaluate the impact of land cover change on LST. A quantitative descriptive method was employed, using a supervised classification approach for land cover mapping, the Mono-Window Brightness Temperature model for LST estimation, and Pearson’s correlation and regression analyses to assess their relationship. The results indicate substantial land cover changes, with a forest area reduction of 26.162 km² and an increase in residential and agricultural land by 16.444 km² and 12.373 km², respectively. In 2016, LST distribution was dominated by the moderate class (20–24 °C), whereas in 2023 it exhibited greater variability, with an expansion of both low-temperature classes (<17 °C and 17–20 °C) and high-temperature classes (24–29 °C). Pearson’s correlation yielded r = −0.523, indicating that forest cover loss correlates with LST increase. Regression analysis suggests that each 1 km² increase in forest cover is associated with a 0.028 °C decrease in LST. These findings underscore the critical role of land cover management in mitigating urban warming.]]>
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