Flujo de trabajo para la obtención de modelos fotogramétricos de alta calidad con time-lapse cameras

Resumo

Using photogrammetric techniques for 3D modelling of natural surfaces has increased significantly in recent years (Eltner, et al. 2016). The easiness of obtaining photographs in an automated way, as well as the low cost of the whole photogrammetric system ensures a great usability when compared to LiDAR point clouds. Currently, there are different software, both com- mercial and open-source, based on Structure-from-motion algorithms allowing the generation of photogrammetric models from multiple images. This communication presents two workflows recently developed to monitor natural slopes. The first algorithm combines the recursive obtaining of photographs, the use of Agisoft Metashape’s Python API, specific processing scripts and contributions of other authors as James Mike (2017) to obtain photogrammetric models with similar resolutions to the models obtained through LiDAR. The second method, called PCStacking, allows photogrammetric models to be obtai- ned more accurately than the standard workflow using low resolution photographs (Raspberry system - 8 Mpx) by stacking 3D models captures sequentially. Both workflows have been developed with the aim of being able to make comparisons and analyses with the highest possible quality.