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StrucNet: a global network for automated vegetation structure monitoring.

Authors :
Calders, Kim
Brede, Benjamin
Newnham, Glenn
Culvenor, Darius
Armston, John
Bartholomeus, Harm
Griebel, Anne
Hayward, Jodie
Junttila, Samuli
Lau, Alvaro
Levick, Shaun
Morrone, Rosalinda
Origo, Niall
Pfeifer, Marion
Verbesselt, Jan
Herold, Martin
Sankey, Temuulen
Murray, Nicholas
Source :
Remote Sensing in Ecology & Conservation; Oct2023, Vol. 9 Issue 5, p587-598, 12p
Publication Year :
2023

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20563485
Volume :
9
Issue :
5
Database :
Complementary Index
Journal :
Remote Sensing in Ecology & Conservation
Publication Type :
Academic Journal
Accession number :
173182282
Full Text :
https://doi.org/10.1002/rse2.333