Abstract This study presents a photogrammetric method for 3D reconstruction of a volcanic plume outline to retrieve its spatial properties. A dataset of sequential multi-view images was collected, using a drone-mounted camera, for a small-scale volcanic plume emitted from Volcan Pacaya, Guatemala. A ‘Space Carving’ algorithm has been applied to estimate the plume shape, top height, volume and drift direction. The complete method workflow is presented herein, including data capture, camera projection, image segmentation, and model reconstruction. The process applied is considered the simplest approach to reconstruct a 3D plume model from sequential imagery, whilst accounting for scene evolution within a probabilistic framework. The algorithm is sensitive to the method of image segmentation, scene resolution and number of images used, with unquantifiable uncertainty in the estimated plume volume due to the lack of ground-truth data. This proof-of-concept investigation confirms that 3D quantification of volcanic plume geometry can be achieved using UAS-based photogrammetry and shows promising results for a new method of measuring volcanic source parameters to validate and adjust dispersion models of volcanic plumes.

中文翻译：

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使用无人航空系统 (UAS) 图像确定火山羽流的三维结构

摘要 本研究提出了一种用于 3D 重建火山羽流轮廓的摄影测量方法，以检索其空间特性。使用无人机安装的相机收集了一个连续多视图图像的数据集，用于从危地马拉火山帕卡亚发出的小规模火山羽流。已应用“空间雕刻”算法来估计羽流形状、顶部高度、体积和漂移方向。本文介绍了完整的方法工作流程，包括数据捕获、相机投影、图像分割和模型重建。所应用的过程被认为是从序列图像重建 3D 羽流模型的最简单方法，同时考虑了概率框架内的场景演变。该算法对图像分割的方法、场景分辨率和使用的图像数量敏感，由于缺乏地面实况数据，估计的羽流体积存在无法量化的不确定性。这项概念验证调查证实，可以使用基于 UAS 的摄影测量法实现火山羽流几何的 3D 量化，并显示出一种新的测量火山源参数方法以验证和调整火山羽流扩散模型的有希望的结果。