Aerial and Terrestrial Photogrammetric Point Cloud Fusion for Intensive Forest Monitoring

Q3 Social Sciences
Stuart Krause
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引用次数: 0

Abstract

Remote sensing methods for forest monitoring are evolving rapidly thanks to recent advances in Unmanned Aerial Vehicle technology and digital photogrammetry. Photogrammetric point clouds allow the non-destructive derivation of individual tree parameters at a low cost. The fusion of aerial and terrestrial photogrammetry for creating full-tree point clouds is of utility for forest research, as tree volume could be assessed more economically and efficiently than by traditional methods. However, this is challenging to implement due to difficulties with co-registration and issues of occlusion. This study explores the possibility of using spherical targets typically used for Terrestrial Laser Scanning to accomplish the co-registration of UAV-based and terrestrial photogrammetric datasets. Results show a full-tree point cloud derived from UAV oblique imagery in combination with terrestrial imagery. Despite issues of noise produced from the sky in terrestrial imagery, the methodology is promising for aerial and terrestrial point cloud fusion.
面向集约森林监测的航空和陆地摄影测量点云融合
由于无人机技术和数字摄影测量的最新进展,森林监测的遥感方法正在迅速发展。摄影测量点云允许以低成本非破坏性地推导单个树的参数。融合航空和陆地摄影测量技术创建全树点云对森林研究具有实用价值,因为与传统方法相比,可以更经济有效地评估树木体积。然而,由于共同注册的困难和遮挡问题,这是具有挑战性的。本研究探索了使用通常用于地面激光扫描的球形目标来完成基于无人机和地面摄影测量数据集的共同配准的可能性。结果显示了由无人机斜向影像与地面影像相结合得到的全树点云。尽管在地面图像中存在来自天空的噪声问题,但该方法在空中和地面点云融合方面很有前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
GI_Forum
GI_Forum Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
23 weeks
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