This paper proposes a new approach for the detection of tree locations around forest machines producing a situational model based on on-site terrestrial LiDAR data collected during harvesting operation. A triangularized ground model is used to planarize the point cloud in order to simplify the tree detection. The planarized ground makes the vertical cutting of the point cloud systematical. Tree stem lines detected from individual trees at individual scan views are used to guide the final alignment into global coordinates. The setup is numerically efficient and does not rely on any positioning and orientation system (POS) based e.g. on an inertial measurement unit (IMU) or global navigation satellite system (GNSS) or wheel rotation counter on the autonomous vehicle.