In the context of China’s carbon peaking and neutrality goals, green space is important for sustaining urban ecosystems, which perform the functions of emission reduction and sequestration enhancement. As a result, the carbon sequestration benefits of urban green space have become an important research topic. Furthermore, carbon sequestration is an important indicator for evaluating the benefits of urban green areas. However, most existing calculation methods are based on manual measurements or satellite remote sensing data, which are inefficient and have low accuracy. Our research develops a method to calculate the carbon sequestration of urban green space vegetation based on point cloud technology and the integrated use of several digital software platforms. First, the point cloud data were acquired by light detection and ranging, and preliminary processing was performed; second, based on the characteristics of urban green space vegetation structure, we used manual segmentation and individual tree segmentation to classify tree, shrub, and ground cover data, and perform voxelization and surface mesh modeling to obtain tree and shrub volume and ground cover three-dimensional surface area; and third, we imported the relevant data using the carbon sequestration calculation formula to obtain the carbon sequestration of each vegetation type and total carbon sequestration of green space vegetation. In the last step, we applied the method to a case study of Mei’an green space in a college campus in Nanjing, China. The proposed method can model vegetation more accurately and efficiently than previous methods and provides an effective way to calculate the carbon sequestration by vegetation in urban green space.