Land-cover change has significant impacts on regional carbon dynamics. Understanding the carbon consequences of land-cover change is necessary for decision makers to address the issues of carbon reduction and climate change mitigation. Optical remote sensing images have been widely used for detecting regional land-cover change. However, it is difficult to acquire desirable images for regions that are frequently affected by cloudy and rainy weather. In this study, we proposed an approach to deal with this problem by integrating moderate-resolution imaging spectroradiometer (MODIS) and Landsat images based on the mixed-label analysis (MLA) model. We tested this model in Guangdong Province, a fast developing sub-tropical region in China, to derive the provincial land-cover data for the analysis of land-cover change between 2000 and 2009 and its impacts on regional carbon dynamics. Results show that forest land decreased by 3.03%, while built-up area rapidly expanded by 73.01% from 2000 to 2009. The regional vegetation carbon sink declined by 2.6%, whereas the regional carbon emissions increased by more than 100% due to the fast urbanization and economic development. The regional vegetation carbon sink can only offset 4.1% of total carbon emissions in 2009, far below the national level (about 7.0–7.7%) at the same period. Future efforts to improve the regional carbon budget should focus more on the control of land development and the advance of energy efficiency.