Complete Workflow for Detailed 3D Forest Reconstruction: From Terrestrial Laser Scanning to Complex 3D Radiative Transfer Modelling

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00216224:14310/25:00142276 RIV/62156489:43410/25:43927658

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Complete Workflow for Detailed 3D Forest Reconstruction: From Terrestrial Laser Scanning to Complex 3D Radiative Transfer Modelling

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Complete Workflow for Detailed 3D Forest Reconstruction: From Terrestrial Laser Scanning to Complex 3D Radiative Transfer Modelling

Popis výsledku anglicky

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

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

in silico Plants

ISSN

2517-5025

e-ISSN

2517-5025

Svazek periodika

7

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

46

Strana od-do

diaf019

Kód UT WoS článku

001593515400001

EID výsledku v databázi Scopus

2-s2.0-105019781385