Terrestrial and mobile laser scanning for national forest inventories: From theory to implementation

Close-range remote sensing; Enhanced NFI; Explorative implementation; Ground-based LiDAR; Point cloud; Tree attribute accuracy; Close range; Enhanced national forest inventory; Ground based; Ground-based light detection and ranging; Light detection and ranging; National forest inventories; Point-clouds; Remote-sensing; Soil Science; Geology; Computers in Earth Sciences

Abstract :

[en] Light Detection and Ranging (LiDAR) has emerged as an important data source for monitoring forest resources. Terrestrial laser scanning (TLS) and Mobile laser scanning (MLS) have already shown high potential in further advancing forest inventory development. By enabling the retrieval of new forest attributes in addition to traditional ones, these technologies could drive forest inventories into a new paradigm by introducing innovative approaches to measuring and monitoring forests. The debate on the possible implementation of TLS and MLS in forest inventories, particularly in national forest inventories (NFIs), continues in both the scientific community and the public institutions. To date, few studies have evaluated the application of TLS and MLS technologies in large-scale forest inventories or assessed their practical operational limits. In this practice-oriented paper, we first detail TLS and MLS data acquisition and processing for tree attribute estimation, assessing their maturity and main limitations. We then explore three European case studies—from the French, Finnish, and Swiss National Forest Inventories (NFIs)—where these technologies have been tested. Based on these experiences, we identify the main constraints and challenges for operational implementation. Lastly, we discuss the prospects for TLS and MLS within the NFI context and the requirements for their successful adoption. We conclude that TLS and MLS should be viewed not as a replacement for, but as a complement to and enhancement of, traditional NFI practices. Emphasis should be placed on the new opportunities these technologies offer, rather than on direct comparisons with conventional methods.

Disciplines :

Phytobiology (plant sciences, forestry, mycology...)

Author, co-author :

Holvoet, Justin ; Université de Liège - ULiège > TERRA Research Centre

Eichhorn, Markus P.; School of Biological Earth and Environmental Sciences, University College Cork, Distillery Fields, North Mall, Ireland ; Environmental Research Institute, Cork, Ireland

Giannetti, Francesca; Department of Agriculture, Food, Environment and Forestry, University of Florence, Florence, Italy

Kükenbrink, Daniel; Swiss Federal Institute for Forest, Birmensdorf, Switzerland

Liang, Xinlian; Wuhan University, Wuhan, China

Mokroš, Martin; Department of Geography, University College London, London, United Kingdom ; Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic ; Faculty of Forestry, Technical University in Zvolen, Zvolen, Slovakia

Novotný, Jan; Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic

Pitkänen, Timo P.; Natural Resources Institute Finland (Luke), Helsinki, Finland

Puliti, Stefano; Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway

Skudnik, Mitja; Slovenian Forestry Institute, Ljubljana, Slovenia ; University of Ljubljana, Biotechnical Faculty, Department of Forestry and Renewable Forest Resources, Ljubljana, Slovenia

More authors (4 more)

Language :

English

Title :

Terrestrial and mobile laser scanning for national forest inventories: From theory to implementation

Publication date :

01 November 2025

Journal title :

Remote Sensing of Environment

ISSN :

0034-4257

eISSN :

1879-0704

Publisher :

Elsevier

Special issue title :

Close-Range Sensing of Forests

Volume :

329

Pages :

114947

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0034425725003517?httpAccept=text/xml

Funding text :

This article/publication is based upon work from COST Action 3DForEcoTech, CA20118, supported by COST (European Cooperation in Science and Technology). A database of available processing solutions for point cloud measurements and pre-processing, both open-source and commercial, has been set up and published on a dynamic website at the COST Action CA20118 platform ( https://3dforecotech.eu/database/ ). An extensive overview of the currently published processing tools, along with their outputs, is provided by Murtiyoso et al. (2024) . The article was partially funded by the COST Action CA20118, grant number E-COST-GRANT-CA20118-a03cbf92. Pitk\u00E4nen, T.P. acknowledges financial support from the Research Council of Finland (decision No. 337655) that enabled him to conduct this study with affiliation to the UNITE Research Flagship. Daniel K\u00FCkenbrink acknowledges financial support through the scientific project \u201CAssessment of the potential of close-range remote sensing to support the Swiss National Forest Inventory\u201D of the Swiss National Forest Inventory. This project was supported by the Swiss Federal Institute of Forest, Snow and Landscape Research (WSL) and the Swiss Federal Office for the Environment (FOEN) .

Available on ORBi :

since 13 August 2025

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