Structure from motion photogrammetry: does the choice of software matter for Ecology?

Structure-from-Motion (SfM) and Multiview-Stereo (MVS) is emerging as a flexible, self-service, remote sensing tool for generating fine-grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone-based SfM+MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM+MVS if it is to fulfil a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer-grade camera was used to capture replicate, centimetre-resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of...

运动恢复结构（Structure-from-Motion, SfM）与多视图立体匹配（Multiview-Stereo, MVS）正逐步发展为地球科学与生态学领域中，用于生成精细数字表面模型（digital surface models, DSMs）的灵活自助式遥感工具。然而，近十年来基于无人机的SfM+MVS应用发展迅猛，当前可供选择的数据处理软件方案已十分多样。因此，学界对软件选择差异引发的可复现性问题，及其对数据质量的影响，尚缺乏充分认知。若要让SfM+MVS作为新型定量遥感工具，为管理框架与物种保护计划提供决策支撑，该认知至关重要。为填补这一知识空白，本研究采用搭载理光GR II（Ricoh GR II）消费级相机的轻型多旋翼无人机，对一片温带集约管理草地生态系统进行重复拍摄，获取了厘米级分辨率的图像数据集。这些数据可用于探索……