A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards.

Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE

Original Publication: Basel, Switzerland : MDPI, c2000-

Trees* ; Algorithms*; Lasers ; Light

Chestnut and chestnut byproducts are of worldwide interest, so there is a constant need to develop faster and more accurate monitoring techniques. Recent advances in simultaneous localization and mapping (SLAM) algorithms and user accessibility have led to increased use of handheld mobile laser scanning (HHLS) in precision agriculture. We propose a tree growth monitoring methodology, based on HHLS point cloud processing, that calculates the length of branches through spatial discretization of the point cloud for each tree. The methodology was tested by comparing two point clouds collected almost simultaneously for each of a set of sweet chestnut trees. The results obtained indicated that our HHLS method was reliable and accurate in efficiently monitoring sweet chestnut tree growth. The same methodology was used to calculate the growth of the same set of trees over 37 weeks (from spring to winter). Differences in week 0 and week 37 scans showed an approximate mean growth of 0.22 m, with a standard deviation of around 0.16 m reflecting heterogeneous tree growth.

Front Plant Sci. 2022 Aug 24;13:951844. (PMID: 36092400)

EDU/875/2021 Junta de Castilla y León; NE/T001194/1 Natural Environment Research Council

Keywords: 3-D point cloud; MLS; SLAM; sweet chestnut; tree growth monitoring

Date Created: 20240328 Date Completed: 20240329 Latest Revision: 20240330

20240330

PMC10975203

10.3390/s24061717

38543985