ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume V-2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 267–271, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-267-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 267–271, 2020
https://doi.org/10.5194/isprs-annals-V-2-2020-267-2020

  03 Aug 2020

03 Aug 2020

SLAM-BASED BACKPACK LASER SCANNING FOR FOREST PLOT MAPPING

J. Shao1,2, W. Zhang3,4, L. Luo5, S. Cai1, and H. Jiang1 J. Shao et al.
  • 1State Key Laboratory of Remote Sensing Science, Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, China
  • 2IRIT, CNRS, University of Toulouse, Toulouse, France
  • 3School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai, China
  • 4Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangdong, China
  • 5Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Keywords: Forest mapping, LiDAR, Backpack laser scanning, Point cloud, SLAM

Abstract. 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.