文章基本信息

标题：SLAM-BASED BACKPACK LASER SCANNING FOR FOREST PLOT MAPPING
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作者：J. Shao ; W. Zhang ; L. Luo 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：V-2-2020
页码：267-271
DOI：10.5194/isprs-annals-V-2-2020-267-2020
语种：English
出版社：Copernicus Publications
摘要：Acquisition of three-dimensional (3D) structural information is significant for forest measurements. To achieve faster data collection in forests, we design a backpack laser scanning (BLS) system using a single mobile laser scanning (MLS) scanner and specific to forest environments. The simultaneous localization and mapping (SLAM) approach based on the natural geometric characteristics of trees is used for BLS-based forest mapping, in which the skeleton line of the individual tree is extracted for scan matching and the incremental maps are adopted for global optimization of all the BLS point clouds. The final experimental results show that the SLAM-based BLS system achieves accurate forest plots mapping and allows reaching low mapping errors, in which the mean errors are approximately 3 cm in the horizontal and 2 cm in the vertical direction.