Discovering Tree Architecture: A Comparison of the Performance of 3D Digitizing and Close-Range Photogrammetry

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F25%3A102328" target="_blank" >RIV/60460709:41320/25:102328 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2072-4292/17/2/202" target="_blank" >https://www.mdpi.com/2072-4292/17/2/202</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs17020202" target="_blank" >10.3390/rs17020202</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Discovering Tree Architecture: A Comparison of the Performance of 3D Digitizing and Close-Range Photogrammetry

Popis výsledku v původním jazyce

Accurate measurement of tree architecture is vital for understanding forest dynamics and supporting effective forest management. This study evaluates close-range photogrammetry (CRP) using TreeQSM (v2.4.1) software, reconstructing 3D tree structures in both deciduous and coniferous species and comparing its performance to the Fastrak 3D digitizing method. CRP proved less labor-intensive and effective for estimating parameters like tree height, stem diameter, and volume of thicker branches in small trees. However, it struggled with capturing intricate structures, overestimating volumetric values and underestimating branch lengths and counts. Mean relative root mean square errors for height, diameter at 0.3 m height, volume, and branch count were 34.19%, 69.9%, 107.87%, and 142.03%, respectively. These discrepancies stem from challenges in reconstructing moving objects and filtering non-woody elements. While CRP shows potential as a complementary method, further advancements are necessary to improve 3D tree model reconstruction, emphasizing the need for ongoing research in this domain.

Název v anglickém jazyce

Discovering Tree Architecture: A Comparison of the Performance of 3D Digitizing and Close-Range Photogrammetry

Popis výsledku anglicky

Accurate measurement of tree architecture is vital for understanding forest dynamics and supporting effective forest management. This study evaluates close-range photogrammetry (CRP) using TreeQSM (v2.4.1) software, reconstructing 3D tree structures in both deciduous and coniferous species and comparing its performance to the Fastrak 3D digitizing method. CRP proved less labor-intensive and effective for estimating parameters like tree height, stem diameter, and volume of thicker branches in small trees. However, it struggled with capturing intricate structures, overestimating volumetric values and underestimating branch lengths and counts. Mean relative root mean square errors for height, diameter at 0.3 m height, volume, and branch count were 34.19%, 69.9%, 107.87%, and 142.03%, respectively. These discrepancies stem from challenges in reconstructing moving objects and filtering non-woody elements. While CRP shows potential as a complementary method, further advancements are necessary to improve 3D tree model reconstruction, emphasizing the need for ongoing research in this domain.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20705 - Remote sensing

Projekt

<a href="/cs/project/TH74010001" target="_blank" >TH74010001: Mapování zdravotního stavu lesů, druhů dřevin a lesních rizik pomocí inovatívnich ICT dat a přístupů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Remote Sensing

ISSN

2072-4292

e-ISSN

2072-4292

Svazek periodika

17

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

001404671800001

EID výsledku v databázi Scopus

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