Abstract. 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 obtain digital surface models and orthophotos ultimately. 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.

中文翻译：

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用于研究滑坡动力学的GNSS和RPAS集成技术：在Victoria and Colinas Lojanas（厄瓜多尔洛哈）地区的应用

摘要。本研究测试了GNSS和RPAS技术在滑坡动力学时空分析中的应用。我们的方法开始于在斜坡表面上建立非永久性GNSS网络，以通过差分GNSS进行定期测量。同样，进行了RPAS飞行以获取高分辨率图像，这些图像使用地面控制点和“运动构造”算法进行了定向和地理参考，从而最终获得了数字表面模型和正射影像。基于GNSS的测量结果，可以精确计算位移的方向和速度，并使用正射照片和DSM来计算整个研究区域中一组重要点的水平和垂直位移，其GNSS数据中的精度高于0.035 m，且精度高于0.10 RPAS数据中的m。这些值在此类研究所需的准确度之内。根据实地观察和摄影测量研究的结果，研究的两个滑坡被归为非常缓慢的流动。