Browsing by Author "Sigua Vizhco, Byron Vinicio"

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    Evaluación de la técnica Structure from Motion para estimar parámetros de arquitectura arbórea
    (Universidad de Cuenca, 2025-08-05) Sigua Vizhco, Byron Vinicio; Iñamagua Uyaguari, Juan Pablo
    Photogrammetry based on the Structure from Motion (SfM) technique presents itself as a viable and accessible alternative to methods such as LiDAR for forest inventories, allowing three-dimensional reconstruction using common cameras at lower cost and with greater flexibility. This study evaluated the applicability of aerial and terrestrial photogrammetry, using drones and mobile phones, as well as developing a simple and functional workflow. Five treatments were applied: T0 (direct field measurement using non-destructive methods), T1 (capture with iPhone LiDAR sensor), T2 (aerial photographs with an RGB drone), T3 (terrestrial photographs with a mobile phone), and T4 (aerial photographs with different configurations). The variables analyzed included total height, crown height, stem volume, crown volume, crown area, diameter at breast height (DBH), and aboveground biomass. In both types of photogrammetry, results showed that there is no single optimal model for all variables; thus, the selection of the most appropriate model depends on the specific parameter to be estimated. In aerial photogrammetry, Model 1 showed the best performance in stem volume, DBH, and aboveground biomass; Model 2 was more accurate for total height, crown height, and crown volume; while Model 3 stood out in calculating crown area. In terrestrial photogrammetry, Model 3 was characterized by higher point density and precision in crown height and DBH; Model 4 excelled in total height; Model 1 in crown volume, crown area, and stem volume; and Model 2 in aboveground biomass. The developed workflow allowed effective estimation, with statistically significant differences observed only in aboveground biomass among treatments. In conclusion, the SfM technique constitutes a precise, viable, and methodologically robust alternative to traditional methods for forest inventories, especially in contexts where optimizing resources without compromising result quality is a priority.