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StrucNet: a global network for automated vegetation structure monitoring

Lookup NU author(s): Dr Marion PfeiferORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2023 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London.Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity. Ecosystem structure is also used as an indirect indicator of habitat quality and expected species richness or species community composition. Spaceborne measurements can provide large-scale insight into monitoring the structural dynamics of ecosystems, but they generally lack consistent, robust, timely and detailed information regarding their full three-dimensional vegetation structure at local scales. Here we demonstrate the potential of high-frequency ground-based laser scanning to systematically monitor structural changes in vegetation. We present a proof-of-concept high-temporal ecosystem structure time series of 5 years in a temperate forest using terrestrial laser scanning (TLS). We also present data from automated high-temporal laser scanning that can allow upscaling of vegetation structure scanning, overcoming the limitations of a typically opportunistic TLS measurement approach. Automated monitoring will be a critical component to build a network of field monitoring sites that can provide the required calibration data for satellite missions to effectively monitor the structural dynamics of vegetation over large areas. Within this perspective, we reflect on how this network could be designed and discuss implementation pathways.

Publication metadata

Author(s): Calders K, Brede B, Newnham G, Culvenor D, Armston J, Bartholomeus H, Griebel A, Hayward J, Junttila S, Lau A, Levick S, Morrone R, Origo N, Pfeifer M, Verbesselt J, Herold M

Publication type: Article

Publication status: Published

Journal: Remote Sensing in Ecology and Conservation

Year: 2023

Pages: epub ahead of print

Online publication date: 14/04/2023

Acceptance date: 27/03/2023

Date deposited: 02/05/2023

ISSN (electronic): 2056-3485

Publisher: John Wiley and Sons Inc


DOI: 10.1002/rse2.333


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Funder referenceFunder name
BB/S014586/1Biotechnology and Biological Sciences Research Council (BBSRC)