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Continuous coastal monitoring using UAV photogrammetry

机译:连续沿海监控使用UAV摄影测量

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The purpose of this study is to collect ortho-images and point clouds acquired from UAVs in February and May to comprehensively assess whether they are suitable for time series offshore monitoring, such as volume change calculation and shoreline extraction. In February and May, UAV photogrammetry was performed at an altitude of 100 m using Zenmuse7 of Inspire-2 for the research area, and 245 chapters and 240 chapters were collected in ground sample resistance (GSD) 1.59 cm and 1.62 cm respectively. We obtained 40 and 21 ground control points (GCPs) that will be used for UAV photogrammetry and TLS surveying by using RTK-GNSS. The collected UAV images were treated as Pix4D mapper software. As a result, we deployed each point cloud and ortho-images in February and May. Image processing showed that the root mean square error (RMSE) in February was 0.015, 0.017, 0.040 m (x, y, z), and in May was 0.018, 0.015, and 0.035 (x, y, z). To verify accuracy, point clouds data collected with TLS surveying were collected. Using TLS point clouds and UAV point clouds (Feb, May), each DEM was deployed and the volume was calculated. In addition, a physical crosssection analysis was performed using 2 lines at the deployed TLS DEM, UAV DEM (2, 5 month). Finally, the coastline for the Imlang beach was extracted by applying the object based image segmentation technique obtained from UAV.
机译:本研究的目的是收集2月份从无人机获得的Ortho-Images和Point云,并可全面评估它们是否适合时间序列海上监测,例如体积变化计算和海岸线提取。 2月和5月,UAV摄影测量在100米的100米的高度下进行,用于研究区域的激励-2,245章和240章分别在接地试样(GSD)1.59cm和1.62cm。我们获得了40和21个地面控制点(GCP),用于通过使用RTK-GNSS来用于UAV摄影测量和TLS测量。收集的UAV图像被视为PIX4D映射器软件。因此,我们于2月和5月部署了每个点云和ortho图像。图像处理表明,2月份的根均方误差(RMSE)为0.015,0.017,0.040M(x,y,z),并且在5月为0.018,0.015和0.035(x,y,z)。要验证准确性,收集了与TLS测量收集的点云数据。使用TLS点云和UAV点云(FEB,5月),部署每个DEM并计算卷。此外,在UAV DEM(2,5个月)的部署的TLS DEM中使用2行进行物理横截面分析。最后,通过应用从UAV获得的基于对象的图像分割技术来提取Imlang Beach的海岸线。

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