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首页> 外文期刊>International journal of remote sensing >Combining Structure from Motion and close-range stereo photogrammetry to obtain scaled gravel bar DEMs
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Combining Structure from Motion and close-range stereo photogrammetry to obtain scaled gravel bar DEMs

机译:结合运动和近距离立体摄影测量的结构以获得缩放的砾石条DEM

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Digital elevation models (DEMs) have been increasingly applied in topographic studies in areas such as physical geography and hydraulic engineering. Several methods have been proposed to reconstruct DEMs, including classic close-range stereo photogrammetry and the more novel Structure from Motion (SfM) methodology. Past published studies tend to apply SfM to large-scale environmental processes, whilst classic close-range stereophotogrammetry is focusing on detailed small-scale applications. However, SfM requires multiple ground control points (GCPs) to allow for proper DEM scaling. The larger the study area, the more GCPs are required, resulting in increased operational complexity and time-consuming application of SfM. As the accuracy of the DEM depends on the equipment used to measure GCPs, this can also result in a cost-expensive operation. In the present study, we introduce a combined SfM and close-range stereo photogrammetry application, with the close-range stereo photogrammetry results serving as a control for providing scale, thus eliminating the need for traditional GCPs. To validate our methodology, we studied a 40 m long gravel bar. We used GoPro Hero 3 cameras for SfM measurements and replaced GCPs by DEMs obtained through close-range stereo photogrammetry with a Nikon D5100 camera pair in stereo. In addition to using photo-mode frames, we also studied the quality of DEMs obtained with GoPro Hero 3 video-mode frames, and show how the DEM quality is reduced due to the smaller image format, hence coarser point cloud spacing, which eventually results in a convex curvature when image overlap was increased. Our results show that it is possible to collect high-quality topographic surface data by only using cameras, and alleviate the need for GCPs. The proposed workflow reduces the complexity, time, and resource demands associated with deploying GCPs and necessary independent geo-referencing, ensuring that digital photogrammetry will continue to gain popularity for field surveying.
机译:数字高程模型(DEM)已越来越多地应用于自然地理和水利工程等领域的地形研究中。已经提出了几种重建DEM的方法,包括经典的近距离立体摄影测量法和更新颖的运动结构(SfM)方法。过去发表的研究倾向于将SfM应用于大规模环境过程,而经典的近距离立体摄影测量法则侧重于详细的小规模应用。但是,SfM需要多个地面控制点(GCP),以实现适当的DEM缩放。研究区域越大,需要的GCP越多,导致操作复杂性增加以及SfM的耗时应用。由于DEM的精度取决于用于测量GCP的设备,因此这也可能导致成本高昂的运行。在本研究中,我们介绍了SfM和近距离立体摄影测量法的组合应用程序,近距离立体摄影测量结果可作为提供刻度的控件,从而消除了对传统GCP的需求。为了验证我们的方法,我们研究了一个40 m长的碎石棒。我们使用GoPro Hero 3相机进行SfM测量,并用尼康D5100立体声相机对通过近距离立体摄影测量法获得的DEM代替了GCP。除了使用照片模式帧外,我们还研究了通过GoPro Hero 3视频模式帧获得的DEM的质量,并说明了由于较小的图像格式,因此点云间距较粗而导致DEM质量降低的情况,最终导致了当图像重叠增加时,凸曲率会变大。我们的结果表明,仅使用照相机就可以收集高质量的地形表面数据,从而减轻了对GCP的需求。拟议的工作流程降低了与部署GCP和必要的独立地理参考相关的复杂性,时间和资源需求,从而确保数字摄影测量学将继续在现场勘测中获得普及。

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