West Pasaman Regency has varied topography that influences land surface temperature (LST) distribution. This study analyzes LST patterns and compares estimates from Landsat 8 and Landsat 9 imagery in 2024 using a quantitative remote sensing approach via Google Earth Engine. LST was derived from thermal infrared bands, while vegetation influence was assessed using NDVI and Pearson correlation. Results show uneven temperature distribution affected by topography, vegetation cover, and land use. Landsat 9 produced slightly higher average temperatures (±30–38 °C) than Landsat 8 (±26–32 °C). A strong correlation was found between both datasets, with a negative correlation between NDVI and LST, indicating that denser vegetation corresponds to lower surface temperatures. Both satellites are suitable for LST analysis, with Landsat 9 showing higher sensitivity.
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