Carbon stock is an important component of terrestrial ecosystems, and its spatial and temporal distribution characteristics and driving mechanisms are of great significance to the advancement of regional sustainable development. Existing studies have mainly focused on the analysis of historical and current carbon stocks, but research on future carbon stocks, especially the portrayal under multiple land use scenarios, is still insufficient. This limitation weakens the practical guidance of carbon stock studies for regional sustainable development goals. In this study, we constructed the MOP-PLUS coupled model, quantitatively predicted the spatial and temporal distribution patterns of land use under four scenarios, namely, the Natural Development Scenarios（NDS）, Ecological Protection Scenarios(EPS), Economic Development Scenarios(EDS), and Sustainable Development Scenarios(SDS) of the Central Yunnan Urban Agglomeration (CYUA), and simulated and assessed the carbon stock in the study area by using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), and described the spatial and temporal evolution characteristics of the study area's carbon stock by using the visualization mapping. The spatial and temporal evolution of carbon stocks in the study area was characterized by visual mapping. Finally, the Optimal Parameters Geographical Detector (OPGD) was used to explore the driving mechanism of the spatial differentiation of carbon stocks, which provides new ideas for optimizing low-carbon development. The results show that: 1) from 2000 to 2020, the carbon stock lost 1. 95×107t cumulatively, of which the loss was particularly serious from 2010 to 2020 due to the accelerated urbanization process; among different land use types, grassland has the highest loss of carbon stock; 2) in the future scenarios, the trend of construction land in all four scenarios shows a continuous growth, and carbon stock In the future scenario, the construction land under all four scenarios shows a continuous growth trend, and the carbon stock decreases. Among them, the ecological protection scenario showed the smallest decrease in carbon stock, with a decrease of 2. 84×106 t, and the economic development scenario showed the largest decrease, with a decrease of 1. 678×107 t. The spatial distributions of carbon stock under the four scenarios were similar, with the high-value areas mainly concentrated in the western and southern parts of the study area, and the low-value areas mainly located in the central part of the study area; 3) Carbon stock was driven by a variety of factors, including normalized vegetative cover, vegetation cover, and vegetation cover. Carbon stock is driven by a variety of influencing factors, among which the Normalized Vegetation Index and the Nighttime Lighting Index are the dominant factors in the spatial variability of carbon stock, while natural and social factors have different degrees of influence on the spatial variability of carbon stock, and human activities play a crucial role in carbon stock changes. The results of this study can provide a theoretical basis for the formulation of the Carbon peaking and carbon neutrality goal and sustainable development goal of the urban agglomeration in central Yunnan, as well as technical support for the evaluation of the implementation of the urban agglomeration's territorial spatial planning.