How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

Land surface temperature (LST) and land albedo (LSA) are the two key regional global climate-controlling parameters; assessing their behavior would likely result in a better understanding of appropriate adaptation strategies to mitigate consequences climate change. This study was conducted explore spatiotemporal variability LST LSA across different use/cover (LULC) classes northwest Iran. To do so, we first applied an object-oriented algorithm 10 m resolution Sentinel-2 images summer 2019 generate LULC map 3284 km2 region Then, computed each class using SEBAL algorithm, which Landsat-8 from winter 2020. The results showed that during season, maximum minimum values were associated with barren (0.33) water bodies (0.11), respectively; value observed for farmland snow cover, forest areas (0.21). acquired rangeland (37 °C) (24 °C), detected forests (4.14 cover (−21.36 respectively. Our revealed residential areas, having summer, able reduce heating effects some extent. Forest due low high LST, particularly winter, had greater effect on warming compared other classes. suggests might not always as much expect.