Noise Analysis for Unbiased Tree Diameter Estimation from Personal Laser Scanning Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F24%3A100510" target="_blank" >RIV/60460709:41320/24:100510 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3390/rs16071261" target="_blank" >http://dx.doi.org/10.3390/rs16071261</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs16071261" target="_blank" >10.3390/rs16071261</a>
Alternative languages
Result language
angličtina
Original language name
Noise Analysis for Unbiased Tree Diameter Estimation from Personal Laser Scanning Data
Original language description
Personal laser scanning devices employing Simultaneous Localization and Mapping (SLAM) technology have rightfully gained traction in various applications, including forest mensuration and inventories. This study focuses the inherent stochastic noise in SLAM data. An analysis of noise distribution is performed in GeoSLAM ZEB Horizon for point clouds of trees of two species, Norway spruce and European beech, to mitigate bias in diameter estimates. The method involved evaluating residuals of individual 3D points concerning the real tree surface model based on TLS data. The results show that the noise is not symmetrical regarding the real surface, showing significant negative difference, and moreover, the difference from zero mean significantly differs between species, with an average of -0.40 cm for spruce and -0.44 cm for beech. Furthermore, the residuals show significant dependence on the return distance between the scanner and the target and the incidence angle. An experimental comparison of RANSAC circle fitting outcomes under various configurations showed unbiased diameter estimates with extending the inlier tolerance to 5 cm with 2.5 cm asymmetry. By showing the nonvalidity of the assumption of zero mean in diameter estimation methods, the results contribute to fill a gap in the methodology of data processing with the widely utilized instrument.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20700 - Environmental engineering
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
2024
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
16
Issue of the periodical within the volume
7.0
Country of publishing house
CH - SWITZERLAND
Number of pages
18
Pages from-to
1-18
UT code for WoS article
001201070000001
EID of the result in the Scopus database
2-s2.0-85190265053