scholarly journals Terrestrial laser scanning to quantify above-ground biomass of structurally complex coastal wetland vegetation

2018 ◽  
Vol 204 ◽  
pp. 164-176 ◽  
Author(s):  
Christopher J. Owers ◽  
Kerrylee Rogers ◽  
Colin D. Woodroffe
2014 ◽  
Vol 6 (2) ◽  
pp. 198-208 ◽  
Author(s):  
Kim Calders ◽  
Glenn Newnham ◽  
Andrew Burt ◽  
Simon Murphy ◽  
Pasi Raumonen ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mathias Disney ◽  
Andrew Burt ◽  
Phil Wilkes ◽  
John Armston ◽  
Laura Duncanson

Abstract Large trees are disproportionately important in terms of their above ground biomass (AGB) and carbon storage, as well as their wider impact on ecosystem structure. They are also very hard to measure and so tend to be underrepresented in measurements and models of AGB. We show the first detailed 3D terrestrial laser scanning (TLS) estimates of the volume and AGB of large coastal redwood Sequoia sempervirens trees from three sites in Northern California, representing some of the highest biomass ecosystems on Earth. Our TLS estimates agree to within 2% AGB with a species-specific model based on detailed manual crown mapping of 3D tree structure. However TLS-derived AGB was more than 30% higher compared to widely-used general (non species-specific) allometries. We derive an allometry from TLS that spans a much greater range of tree size than previous models and so is potentially better-suited for use with new Earth Observation data for these exceptionally high biomass areas. We suggest that where possible, TLS and crown mapping should be used to provide complementary, independent 3D structure measurements of these very large trees.


2021 ◽  
Vol 41 (19) ◽  
Author(s):  
苟芳珍,赵成章,杨俊仓,任杰,马俊逸,李子琴 GOU Fangzhen

2021 ◽  
Author(s):  
Daniel Kükenbrink ◽  
Oliver Gardi ◽  
Felix Morsdorf ◽  
Esther Thürig ◽  
Andreas Schellenberger ◽  
...  

<p>Trees supply a multitude of ecosystem services (e.g. carbon storage, suppression of air pollution, oxygen, shade, recreation etc.) not only in forested areas but also in urban landscapes. Many of these services are positively correlated with tree size and structure. The assessment of carbon storage potential via the quantification of above ground biomass (AGB) is of special importance. However, quantification of AGB is difficult and applied allometries are often based on forest trees, which are subject to very different growing conditions, competition and form compared to urban trees. In this contribution, we highlight the potential of terrestrial laser scanning (TLS) techniques to extract high detailed information on tree structure and AGB with a focus on urban trees.</p><p>A total of 55 urban trees distributed over eight cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighted. Tree structure, volumes and AGB from the TLS point clouds were extracted using Quantitative Structure Modelling (QSM). TLS derived AGB estimates were compared to allometric estimates dependent on diameter at breast height only. The allometric models were established within the Swiss National Forest Inventory and are therefore optimised for forest trees.</p><p>TLS derived AGB estimates showed good performance when compared to destructively harvested references with an R<sup>2</sup> of 0.954 (RMSE = 556 kg), compared to an R<sup>2</sup> of 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB.</p><p>The presented results show that TLS based wood volume estimates show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate, non-destructive AGB estimates that could be used to establish new allometric equations without the need of extensive destructive harvest.</p>


2011 ◽  
Vol 151 (10) ◽  
pp. 1305-1311 ◽  
Author(s):  
Dominik Seidel ◽  
Friderike Beyer ◽  
Dietrich Hertel ◽  
Stefan Fleck ◽  
Christoph Leuschner

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