使用无人机摄影测量在亚齐省甘榜兰克林的地面运动的时空分析

Nabila Amalia, S. Syamsidik, N. Ismail
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引用次数: 0

摘要

地面运动是造成印尼重大损失的最常见灾害之一。无人机(UAV)作为一种获取地面运动详细特征的快速观测方法已得到广泛应用。通常,活动滑坡区域很难进入。这妨碍了对地面运动的密切监测和观察。本研究旨在演示使用无人机作为监测和观测地面活动区域的工具,并验证结果。为此,该研究在印度尼西亚亚齐省的Gampong Lamkleng进行,使用无人机摄影测量技术进行时空分析。选择无人机是因为它易于使用,实用,并且对于相对较小且难以到达的滑坡区域安全。利用Agisoft Metashape软件对航拍照片进行建模处理,并利用量子地理信息系统(QGIS)和ArcGis进行分析。观测结果表明,2021年1月20 ~ 23日发生了最大的地面移动,这与附近雨量站测量的降水率有关。移动量为1411.063 m3,受暴雨影响地面移动速率达到0.69 m/d。估计损失价值为1 055 854 000印尼盾。将无人机图像分析与使用实时运动学(RTK)测量的实际地面高程进行比较。验证结果表明,摄影测量法与RTK测量法的精度达到了99%。另外,对19个检查点进行均方根误差分析,发现准确率仍然很低。RMSE值低是由于没有使用地面控制点进行地理参考过程。
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Spatio-Temporal Analysis of Ground Movement Using Unmanned Aerial Vehicle Photogrammetry in Gampong Lamkleng, Aceh Besar
Ground movement is one of the most frequent disasters causing major damages in Indonesia. Unmanned Aerial Vehicle (UAV) has been widely used as a rapid observation method to obtain detailed characterization of ground movement. Often, active landslide area is difficult to access. This hinders close monitoring and observations of the ground movement. This study aims to demonstrate the use of UAV as tools for monitoring and observations on active ground movement area and to validate the results. For this purpose, the study was conducted at Gampong Lamkleng, Aceh Besar-Indonesia using spatio-temporal analysis by UAV photogrammetry. The UAV was chosen because it is easy to use, practical, and safe for landslide area that are relatively small and difficult to reach. Aerial photographs were processed using the Agisoft Metashape software in modeling and analyzed using Quantum GIS (QGIS) and ArcGis. The observation results show that the largest ground movement occurred in January 20 to 23, 2021 which was related to precipitation rates measured at a nearby rainfall station. The movement volume was 1,411.063 m3 and a rate of ground movement reaching 0.69 m/day due to heavy rain. The estimated value of losses is IDR 1,055,854,000. The UAV images analysis were compared to actual ground elevation measured using Real-Time Kinematic (RTK). The validation show that the accuracy based on comparison between photogrammetric and RTK measurement was at agreeable rate (99%). Otherwise, the accuracy performed on 19 check point using Root Mean Square Error analysis found that the accuracy was still very low. The low RMSE value is due to the georeferencing process using the Ground Control Point not being carried out.
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