It is of great significance for evaluating the aboveground carbon (AGC) storage of vegetation and their dynamics changes rapidly and accurately for assessing the carbon sequestration capacity of forests. This study took the forest in Huanglong Mountain of Shaanxi Province as the research object, based on the field measured data of the sample plot and satellite remote sensing data, and established a model of AGC stock of vegetation in Huanglong Mountain Forest District, so the long-term AGC storage model of forest vegetation in the study area was realized from 2000 to 2021. And the model realized the inversion of AGC of forest vegetation in the study area, and based on it, the spatio-temporal research of the AGC from 2000 to 2021 in the study area was carried out. The research results showed that:(1) the average AGC of forest vegetation in Huanglong Mountain had a fluctuating upward trend, and the carbon stock was higher than the average level of the whole province. (2) The eastern, southern, central and northwestern parts of the study area were the areas with high values of AGC and it showed an increasing trend, while the AGC of vegetation in the northeastern, western and southwestern parts of the study area was low, and showed a decreasing trend. The AGC of forest vegetation in the study area had increased in 22 years and the productivity had improved to a certain degree. (3) Annual average temperature, annual evapotranspiration, annual precipitation and elevation were the main factors affecting the spatial variation of AGC of forest vegetation in the study area from 2000 to 2021. The interaction between any two factors had a significant greater impact on the AGC of forest in Huanglong Mountain than the individual factor, which indicating that the spatial distribution of AGC of forest vegetation in Huanglong Mountain was affected by a combination of the factors in different time and space. The influence of annual precipitation on its spatial distribution was gradually decreased and the forest stability was improved during the research period. The study proposed a method for quickly estimating the AGC of regional vegetation on the basis of the limited information, and understood the spatial and temporal variation of the AGC in regional forest vegetation and its driving factors that affecting its change, which provided an important basis for grasping the information of AGC of regional vegetation and assessing the carbon sequestration capacity of forests.