A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
An integrated approach combining bi-temporal airborne laser scanning and X-ray microdensitometry in assessing wood properties
Tekijät: Poorazimy, Maryam; Ronoud, Ghasem; Yrttimaa, Tuomas; Hyyppä, Juha; Saarinen, Ninni; Kankare, Ville; Vastaranta, Mikko
Kustantaja: Elsevier BV
Julkaisuvuosi: 2025
Journal: Forest Ecology and Management
Tietokannassa oleva lehden nimi: Forest Ecology and Management
Artikkelin numero: 122497
Vuosikerta: 585
ISSN: 0378-1127
eISSN: 1872-7042
DOI: https://doi.org/10.1016/j.foreco.2025.122497
Verkko-osoite: https://doi.org/10.1016/j.foreco.2025.122497
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/485145214
Information on wood properties across trees and stands is needed to support silviculture and wood procurement. Wood properties of standing trees are usually measured by destructive sampling limiting the number of observations that can be collected across a range of forest structural and environmental conditions. In contrast, airborne laser scanning (ALS), with its capability to characterize tree crowns and their increment over time, could provide a non-destructive approach for assessing wood properties. This study aimed at relating ALS-derived mean annual increments in tree height and crown dimensions between 2009 (T1) and 2023 (T2) to X-ray microdensitometry-measured mean ring width (RWmean-tree) and basal-area weighted mean wood density (WDmean-tree) formed during the same period. The experimental design comprised 257 Scots pines (Pinus sylvestris L.) and 142 Norway spruces (Picea abies (L.) Karst.) across 59 sample plots representing varying boreal forest conditions. As per our investigations, the mean annual increment in tree height (ΔHmean_tree) represented the strongest correlations with RWmean_tree for both tree species (r = 0.43–0.44) and a weak but statistically significant correlation with WDmean_tree for Norway spruces only (r = −0.17). When aggregating individual tree observations for plot-level, ΔHmean_plot exhibited moderate correlations (r = 0.47–0.48) with RWmean_plot for both species. WDmean_plot of Scots pines showed a correlation of 0.36 with the averaged mean annual increments of crown surface area. However, none of the metrics were significant for WDmean_plot of Norway spruces. By utilizing the linear-mixed effect model 40–41 % of the variations in RWmean_tree of Scots pines and Norway spruces could be explained when accounting for the variability between sample plots. Based on our study, it appears that some of the variation in wood properties, particularly in ring width, can be captured using bi-temporal ALS measurements. However, assessing wood properties over large areas remains challenging and requires further research.
Ladattava julkaisu This is an electronic reprint of the original article. |
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The authors would like to acknowledge financial support by the Research Council of Finland through Forest–Human–Machine Interplay flagship of science [decision number 337127], Density4Trees project [decision number 331711], and Scan4erstEcosystem Research Infrastructure [decision number 337810 and 346383]. Thanks also go to Jarmo Pennala, laboratory specialist at UEF School of Forest Sciences, for analyzing wood samples.