In this paper, a LiDAR simultaneous localization and mapping (SLAM) pose optimization algorithm is proposed based on graph optimization theory and global navigation satellite system (GNSS) data. By adding the satellite positioning node into the pose graph, the trajectory error can be effectively controlled within the range of GNSS positioning error when there is no loopback. In long distance loopback, the loopback detection point can be accurately located, which improves the global consistency of the LiDAR SLAM pose graph. The proposed algorithm is tested in the urban environment with better rigidity and in the non-urban environment with weaker rigidity. Experimental results show that the trajectory drift can be controlled to be about 1 m for 300 m straight-line mapping when there is no loopback. In the case of long distance (above 360 m) loopback, the proposed algorithm controls the trajectory drift to be within 0.2 m and about 0.1 m for the primary and the secondary loopback,respectively. These results fully demonstrate the effectiveness of the proposed algorithm.