Simultaneous Localization and Mapping (SLAM) is a real-time approach using a mobile robot platform to capture a map of the environment, while simultaneously localizing the robot in relation to its environment. For this purpose, the robot is usually equipped with navigation sensors such as IMU or odometers, while laser scanners and/or monocular, stereo or RGB-D cameras are used to observe the surroundings. Similar to the well-known Structure-from-Motion approach, the simultaneous orientation of the camera and/or laser scanner with respect to the 3D map of the environment uses a photogrammetric bundle block adjustment. Basic observation are corresponding pixels and/or laser scans for the respective camera or LiDAR stations. SLAM processes have meanwhile reached a remarkable level of development. They are integrated in a considerable number of applications and are becoming more and more important for geodetic measuring tasks, especially while aiming at data collection in real-time. Our contribution demonstrates and discusses the potential of SLAM methods for such geodetic tasks on examples of current projects such as the monitoring of a construction site using cameras mounted on a crane and mobile 3D mapping of indoor environments.