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Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques

机译:利用无人机和摄影测量技术分析影响橄榄树的滑坡演化

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This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many environmental applications like landslide research. The methodology starts with the execution of UAV flights to acquire very high resolution images, which are oriented and georeferenced by means of aerial triangulation, bundle block adjustment and Structure from Motion (SfM) techniques, using ground control points (GCPs) as well as points transferred between flights. After Digital Surface Models (DSMs) and orthophotographs were obtained, both differential models and displacements at DSM check points between campaigns were calculated. Vertical and horizontal displacements in the range of a few decimeters to several meters were respectively measured. Finally, as the landslide occurred in an olive grove which presents a regular pattern, a semi-automatic approach to identifying and determining horizontal displacements between olive tree centroids was also developed. In conclusion, the study shows that landslide monitoring can be carried out with the required accuracy—in the order of 0.10 to 0.15 m—by means of the combination of non-invasive techniques such as UAV, photogrammetry and geographic information system (GIS).
机译:本文探讨了无人飞行器(UAV)技术和高分辨率摄影测量技术在研究影响橄榄树的滑坡演变过程中的应用。在过去的十年中,无人飞行器得到了广泛的应用,该技术在许多环境应用(例如滑坡研究)中正在明显发展。该方法从执行无人机飞行开始,以获取非常高分辨率的图像,这些图像通过空中三角测量,束块调整和运动结构(SfM)技术进行定位和地理参考,并使用地面控制点(GCP)和点在航班之间转移。获得数字表面模型(DSM)和正射照片后,可以计算运动之间的差分模型和DSM检查点的位移。分别测量了几分米到几米范围内的垂直和水平位移。最终,由于滑坡发生在呈现规则规律的橄榄树丛中,因此开发了一种用于识别和确定橄榄树质心之间水平位移的半自动方法。总之,研究表明,通过结合无人飞行技术,无人机,摄影测量法和地理信息系统(GIS),可以以所需的精度(在0.10至0.15 m的数量级)进行滑坡监测。

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