Mobile laser scanning in support of national and regional forest inventories

In the context of a growing need to diversify forest information, national and regional forest inventories (NFI and RFI) could benefit from mobile Light Detection and Ranging (LiDAR) technologies. Ground-based mobile laser scanning (MLS) and unmanned aerial laser scanning (ULS) can potentially retrieve a large panel of forest attributes quickly, efficiently, and accurately. In this study, conducted in Wallonia (southern Belgium), we aimed to evaluate, in the context of an NFI, the accuracy of MLS at tree, plot, and inventory levels and the potential benefits of fusing ULS with MLS. In total, 60 circular forest plots of 0.1 ha containing 2,497 trees were measured by traditional inventory means and scanned using MLS. Among them, 27 were additionally scanned by ULS, and ULS and MLS scans were fused to produce an enhanced point cloud. We then evaluated the accuracy of MLS considering, at tree level, the diameter at breast height, total height, merchantable wood volume, and crown projected area and volume; at plot level, the total merchantable wood volume, number of trees, and total basal area; and for the whole inventory, the total volume and number of trees. Tree, plot, and inventory metrics were accurately acquired with a strong correlation to field measurements ( r 2 ranging from 0.83 to 0.98). Out of all estimated metrics, height has a potential accurately estimated by MLS than by field measurements. The fusion of ULS and MLS allowed for a more accurate crown measurement, but height estimation was not significantly better than with MLS scan alone. The accuracy of soft- and hardwood forest plot estimations differed considering total plot wood volume, number of trees, and individual tree height. In this study, we explored the possibility and limitations of MLS in undertaking large-scale inventory in terms of accuracy, time, and reliability. • We retrieved traditional NFI attributes within 60 0.1ha plots using MLS. • With the same methods, MLS accuracy differs between hardwood and softwood forests. • Forest structure influences the estimation of total plot wood volume. • In leaf of conditions, ULS didn’t allow a more precise tree height estimation

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Publication Details

Journal
Science of Remote Sensing
Published
2025-10-18
DOI
https://doi.org/10.1016/j.srs.2025.100316
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Mobile laser scanning in support of national and regional forest inventories

Science of Remote Sensing
Remote Sensing and LiDAR Applications
article

Mobile laser scanning in support of national and regional forest inventories

article en

Abstract

In the context of a growing need to diversify forest information, national and regional forest inventories (NFI and RFI) could benefit from mobile Light Detection and Ranging (LiDAR) technologies. Ground-based mobile laser scanning (MLS) and unmanned aerial laser scanning (ULS) can potentially retrieve a large panel of forest attributes quickly, efficiently, and accurately. In this study, conducted in Wallonia (southern Belgium), we aimed to evaluate, in the context of an NFI, the accuracy of MLS at tree, plot, and inventory levels and the potential benefits of fusing ULS with MLS. In total, 60 circular forest plots of 0.1 ha containing 2,497 trees were measured by traditional inventory means and scanned using MLS. Among them, 27 were additionally scanned by ULS, and ULS and MLS scans were fused to produce an enhanced point cloud. We then evaluated the accuracy of MLS considering, at tree level, the diameter at breast height, total height, merchantable wood volume, and crown projected area and volume; at plot level, the total merchantable wood volume, number of trees, and total basal area; and for the whole inventory, the total volume and number of trees. Tree, plot, and inventory metrics were accurately acquired with a strong correlation to field measurements ( r 2 ranging from 0.83 to 0.98). Out of all estimated metrics, height has a potential accurately estimated by MLS than by field measurements. The fusion of ULS and MLS allowed for a more accurate crown measurement, but height estimation was not significantly better than with MLS scan alone. The accuracy of soft- and hardwood forest plot estimations differed considering total plot wood volume, number of trees, and individual tree height. In this study, we explored the possibility and limitations of MLS in undertaking large-scale inventory in terms of accuracy, time, and reliability. • We retrieved traditional NFI attributes within 60 0.1ha plots using MLS. • With the same methods, MLS accuracy differs between hardwood and softwood forests. • Forest structure influences the estimation of total plot wood volume. • In leaf of conditions, ULS didn’t allow a more precise tree height estimation

Science of Remote SensingVol. 12
Gembloux Agro-Bio Tech (BE), Swiss Federal Institute for Forest, Snow and Landscape Research (CH)
Université de Liège, Interreg
Life in Land
Openalex Percentile: Top 50%
Remote Sensing and LiDAR Applications
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