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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • 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

    <a href="/en/project/TH74010001" target="_blank" >TH74010001: Mapping of forest health, species and forest risks using Novel ICT Data and Approaches</a><br>

  • Continuities

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

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

    Remote Sensing

  • ISSN

    2072-4292

  • e-ISSN

    2072-4292

  • Volume of the periodical

    17

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    18

  • Pages from-to

    1-18

  • UT code for WoS article

    001404671800001

  • EID of the result in the Scopus database