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This specific characteristic enables its real time use on the standard mobile devices. a specific particle filter has been designed to enable good position estimations by a small number of particles (e.g. Positioning is achieved by a pedestrian dead reckoning approach, i.e. For this aim, a navigation system able to deal with the unavailability of the GNSS (e.g. emergency conditions, when also WiFi connection might not work). The goal is to make this MMS usable and reliable even in difficult environments (e.g. This paper considers the use of a low cost mobile device in order to develop a mobile mapping system (MMS), which exploits only sensors embedded in the device.

The method is intended to be used in tree measurements for forest inventory or other outdoor measuring. Accuracy can be improved by using a scale bar of known length placed in the scene. The results pointed to scale accuracy of around 3%, which may be acceptable for many applications. Several tests were carried out both in open sky and under trees, with worse conditions for GPS positioning. The aim of the study is to assess the geometric accuracy of such methodology, especially in relative terms, in the evaluation of object dimensions.

The model becomes georeferenced by means of the camera positions which are recorded by the camera navigation GPS receiver. The method implemented uses the Structure from Motion approach in order to obtain the 3D model. These cameras are very small and can be used by any operator, even in other forestry works, to collect imagery for photogrammetric post processing. This paper presents a study of the application of action cameras, such as the GoPro, for the extraction of 3D models in a forest environment. The system can be improved in several forms, through processing techniques, such as structure from motion, but without the incorporation of additional hardware. Tests carried out in a sparse urban environment have shown planimetric accuracy better than 40cm, appropriate for large scale mapping, such as 1:2000. Positions of observed objects, such as traffic signs, are derived from consecutive frames. Assuming the car moves in a horizontal plane and the camera has no significant tilts, the system is treated in planimetric terms, with camera axis azimuth derived from the vehicle trajectory. The precise time of individual frames is obtained from the camera GPS and positions are interpolated from the GNSS receiver. Within good observation conditions, without tall buildings, differential positioning (either RTK or PPK) provides the trajectory with accuracy of a few centimetres. Although the system can be dependent on the camera GPS positions only, it was developed to include a GNSS dual frequency receiver, carried inside the car, on the dashboard. This paper describes the implementation of a mobile mapping system, based on a GoPro Hero 5 camera mounted on the side rearview mirror of a car. That is the case of the very popular camera, Gopro Hero 5. Recent models include GPS, which can deliver position and time of individual images and video frames. Action cameras can operate in outdoor conditions, such as outside a car, and provide good quality imagery that can be exploited to collect geospatial data by photogrammetric means.