This paper is concerned with generating and application of point clouds gathered via Google Tango, a technology based on the principles of Depth Perception, Motion Tracking, and Area Learning, while simultaneously controlling the trajectory accuracy. This involves applying the SLAM (Simultaneous Localisation and Mapping) in real conditions. There are two main goals to the paper: 1: Generating, preparing, and evaluating the point clouds gathered by Lenovo Phab 2 Pro. We were mainly concerned with data collecton methods, with the particular objective of determining the diameter of trees at a given height (d1,3). The diameters were determined by manual measurements in the cloud point genereated by RTAB-Map and further evaluated by CloudCompare. Calliper-measured diameters would be used for reference. 2: Generating, preparing, and evaluating of the trajectory of Lenovo Phab 2 Pro, with a subsequent comparison to the trajectory of INS. Location logging for trajectory measurements was executed at two different frequences (1Hz, 5Hz). Preparation and exportation of the trajectories were done in RTAB-Map, the subsequent evaluation in QDIS. For reference, we would use the actual INS trajectory, and a set of control points measured with the help of an electronic tachymeter. The precision of the measurements thus acquired is comparable to several other noncontact methods, although establishing the possibility of automation requires further research. Evaluation of trajectory precision had its own set of methodological problems (eg. georeferencing and time synchronization), and these will have to be adressed in further research.