GNSS and RPAS Integration Techniques for Studying Landslide Dynamics: Application to the Areas of Victoria and Colinas Lojanas, (Loja, Ecuador) Zárate, Belizario A. El Hamdouni Jenoui, Rachid Fernández, Tomás RPAS GNSS Landslides Dynamics DSM Accuracy Loja (Ecuador, Provincia) Ecuador GCP SfM Measurements This research received no external funding. This study has the support of the Private Technical University of Loja through the internal research project PROY_GMIC_1285. This research tests the application of GNSS and RPAS techniques to the spatiotemporal analysis of landslide dynamics. Our method began by establishing non-permanent GNSS networks on the slope surfaces to perform periodic measurements by differential GNSS. Similarly, RPAS flights were made to acquire high-resolution images, which were oriented and georeferenced using ground control points and structure-from-motion algorithms to ultimately obtain digital surface models and orthophotos. Based on GNSS measurements, the direction and velocity of displacements were accurately calculated, and orthophotos and DSMs were used to calculate horizontal and vertical displacements in a set of significant points throughout the study area, reaching accuracies higher than 0.035 m in the GNSS data and 0.10 m in the RPAS data. These values were within the accuracy required for such studies. Based on the field observations and the results from the photogrammetric studies, the two studied landslides were classified as very slow flows. These techniques are the basis for establishing early warning systems in areas of natural hazards based on the calculation of displacement speeds of the surface of slopes. 2021-10-15T09:00:33Z 2021-10-15T09:00:33Z 2021-09-03 journal article Zárate, B.A.; El Hamdouni, R.; Fernández, T. GNSS and RPAS Integration Techniques for Studying Landslide Dynamics: Application to the Areas of Victoria and Colinas Lojanas, (Loja, Ecuador). Remote Sens. 2021, 13, 3496. [https://doi.org/10.3390/rs13173496] http://hdl.handle.net/10481/70877 10.3390/rs13173496 eng http://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España MDPI