Global warming is one of the most daunting challenges that our humanity is facing. It has urged the action to study carbon emissions and carbon sequestration ability to control the regional climate change. Some studies show that human activities, especially the combustion of fossil fuel, cause the carbon emissions and the global climate warming. Therefore, it is important to work on energy saving and emission reduction. At the same time, the carbon sink capacity of forest, grassland, crops and other vegetations become one of the most powerful approaches to ease the global climate change. Thus, we conduct a research in this area, in order to improve the carbon source utilization efficiency, reduce the carbon intensity, prefect the energy-saving and emission-reduction works, and well manage the carbon budget capacity and some other problems. Taking Youjiang district of Baise city in Guangxi Province as the experimental area, this article uses the object-oriented classification technology and extracts the area geographic information from the Landsat 8 OLI and Google Earth images. Due to the complex terrain of the study area, different parameter settings of the multi-scale segmentation are used and the optimal scaling for the image segmentation is selected. We also use the membership function method, the closest classification method and the CART decision tree classifier method to complete the object-oriented classification layer by layer and evaluate the accuracy of the classification results, based on the spectral difference, geometric shapes, objects, texture and other characteristics. Through summarizing the conversion relationship between the land and carbon coefficient, combining with the high-precision object-oriented classification results, the estimation model of carbon budget capacity is built based on land-cover types. Finally, according to the CASA model of carbon budget capacity, we check the accuracy of the estimation method. The carbon budget capacity of Youjiang district is estimated to be -3996.4 kt, according to the coefficient that corresponds to the feature carbon conversion relationship. Integrated with the administrative planning, population distribution, DEM, and other relevant data, the carbon budget capacity of Youjiang district is analyzed thematically. The results showed that: (1) the use of RS and GIS technologies in the studies of regional carbon budget capacity reveals a distinct advantage. The multiscale segmentation and object classification method can efficiently eliminate the extraction error caused by spectral confusion, and solve problems such as the large quantity of spatial data faced by the traditional classification, the classification of "salt and pepper", the exact utilization of different classification methods, and the improvement of the classification accuracy of carbon. (2) We summarized the findings of the coefficients for carbon balance capacity from domestic and international researches, and applied it in the construction of carbon balance estimation model.