Rapid urbanization is changing the existing patterns of land use land cover (LULC) globally, which is consequently increasing the land surface temperature (LST) in many regions. The present study is focused on estimating current and simulating future LULC and LST trends in the urban environment of Chaoyang District, Beijing. Past patterns of LULC and LST were identified through the maximum likelihood classification (MLC) method and multispectral Landsat satellite images during the 1990–2018 data period. The cellular automata (CA) and stochastic transition matrix of the Markov model were applied to simulate future (2025) LULC and LST changes, respectively, using their past patterns. The CA model was validated for the simulated and estimated LULC for 1990–2018, with an overall Kappa (K) value of 0.83, using validation modules in IDRISI software. Our results indicated that the cumulative changes in built-up to vegetation area were 74.61 km2 (16.08%) and 113.13 km2 (24.38%) from 1990 to 2018. The correlation coefficient of land use and land cover change (LULCC), including vegetation, water bodies and built-up area, had values of r =  − 0.155 (p > 0.005), −0.809 (p = 0.000), and 0.519 (p > 0.005), respectively. The results of future analysis revealed that there will be an estimated 164.92 km2 (−12%) decrease in vegetation area, while an expansion of approximately 283.04 km2 (6% change) will occur in built-up areas from 1990 to 2025. This decrease in vegetation cover and expansion of settlements would likely cause a rise of approximately ∼10.74 °C and ∼12.66 °C in future temperature, which would cause a rise in temperature (2025). The analyses could open an avenue regarding how to manage urban land cover patterns to enhance the resilience of cities to climate warming. This study provides scientific insights for environmental development and sustainability through efficient and effective urban planning and management in Beijing and will also help strengthen other research related to the UHI phenomenon in other parts of the world.

Rapid urbanization poses a threat to various ecosystem services. Beijing has undergone extensive infrastructure development in recent years. The study aims to extract land surface temperature (LST) and land use cover (LUC) data from satellite imagery, identify urban heat island (UHI) areas in Beijing, and determine the correlation between LST, LUC, NDVI, and BUI. It will also investigate the relationship between UHI and built/unbuilt areas, evaluate thermal comfort in Beijing using UTFVI, and assess the ecological quality of different land use types using the Ecological Evaluation Index (EEI). The results can inform urban planning and management in rapidly urbanizing and climate-changing regions. Changes in LUC and other activities affect the distribution of LST. For the study years (2005–2020), the estimated mean LST in Beijing was 24.72 °C, 27.07 °C, 26.22 °C, and 27.03 °C, respectively. A significant positive correlation (r = 0.96 p > 0.005) was found between LST and urban areas with other infrastructures. Geographically weighted regression (GWR) outperformed with Adj R2 > 0.74, suggesting that the extent of an urban heat island (UHI) is strongly dependent on the settlements, LUC composition, size, and terrain of surrounding communities. Urban hotspots in the city were identified and validated using Google Earth imagery. The Ecological Evaluation Index (EEI) value was relatively low compared to other ecosystem-related units. EEI showed a continuous increase of six percent in the most negative categories, indicating an unstable environment. This study concludes that urbanization affects the city’s environment, and study findings would help to regulate the urban ecosystem in Beijing.