Complete Workflow for Detailed 3D Forest Reconstruction: From Terrestrial Laser Scanning to Complex 3D Radiative Transfer Modelling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F25%3A00639585" target="_blank" >RIV/86652079:_____/25:00639585 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/25:00142276 RIV/62156489:43410/25:43927658
Result on the web
<a href="https://academic.oup.com/insilicoplants/advance-article/doi/10.1093/insilicoplants/diaf019/8266334?login=false" target="_blank" >https://academic.oup.com/insilicoplants/advance-article/doi/10.1093/insilicoplants/diaf019/8266334?login=false</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/insilicoplants/diaf019" target="_blank" >10.1093/insilicoplants/diaf019</a>
Alternative languages
Result language
angličtina
Original language name
Complete Workflow for Detailed 3D Forest Reconstruction: From Terrestrial Laser Scanning to Complex 3D Radiative Transfer Modelling
Original language description
High-resolution 3D forest representations are essential for remote sensing applications such as above-ground biomass estimation using radiative transfer modelling. However, existing reconstruction approaches are often time-consuming and rely heavily on manual input.nA comprehensive and largely automated end-to-end workflow is presented for reconstructing realistic 3D forest representations from terrestrial laser scanning (TLS) data. The workflow includes five main steps: segmentation of individual trees, semantic classification into wood and foliage using a custom-trained PointNet++ model, reconstruction of woody structures via Quantitative Structure Models, biologically realistic foliage placement, and spatial distribution of trees. Reconstructed forest plots from Central Europe were used to simulate airborne laser scanning (ALS) data in Helios++.nThe results were validated against real ALS acquisitions. The simulated data showed strong agreement with real ALS data across key forest structure metrics, with correlations ranging from R² = 0.46 for height standard deviation to R² = 0.96 for mean canopy height, with corresponding nRMSE values ranging between 23.2% and 12.6%. The largest discrepancies occurred in upper canopy regions due to TLS occlusion effects, where dense vegetation blocked the scanner's line of sight, resulting in these areas being underrepresented in the reconstructed 3D scenes.nThese results demonstrate that detailed 3D forest reconstructions can be achieved with minimal manual inputs, providing a robust basis for radiative transfer modelling and the generation of synthetic remote sensing datasets, which are critical for improving forest monitoring and carbon stock assessments.n
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20705 - Remote sensing
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
in silico Plants
ISSN
2517-5025
e-ISSN
2517-5025
Volume of the periodical
7
Issue of the periodical within the volume
2
Country of publishing house
GB - UNITED KINGDOM
Number of pages
46
Pages from-to
diaf019
UT code for WoS article
001593515400001
EID of the result in the Scopus database
2-s2.0-105019781385