Abstract: Based on Landsat remote sensing imagery and sample plot data from 2021, this study estimated the aboveground carbon stock of Pinus densata in Shangri-La City. The optimal model was used to estimate the aboveground carbon stock of Pinus densata, and the obtained stand age data were further used to analyze the distribution of aboveground carbon density and carbon stock across different stand age classes. The results show that: Among the five constructed estimation models , the XGBoost model has the highest prediction accuracy, with an R² of 0.91, an RMSE of 6.43 t/hm², an rRMSE of 17.65%, and a P_pred value of 81.03%. Based on the optimal model, the estimation and inversion of aboveground carbon density of Pinus densata were conducted, yielding a minimum value of 9.63 t/hm², a maximum value of 89.26 t/hm², and a total carbon stock of approximately 7607333.96 t for Pinus densata in Shangri-La City. Analysis of the carbon density variation between adjacent age classes reveals that the most significant increase in carbon density occurs from young forests to middle-aged forests, reaching 3.11 t/hm², with subsequent variations showing a gradual decline.Overall, both carbon density and total carbon stock of Pinus densata forests in Shangri-La City increased continuously with increasing forest age, whereas the rate of increase in carbon density gradually slowed.