Inventory of close-to-nature forest stands using terrestrial mobile laser scanning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F22%3A94385" target="_blank" >RIV/60460709:41320/22:94385 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1569843222002928" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1569843222002928</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jag.2022.103104" target="_blank" >10.1016/j.jag.2022.103104</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Inventory of close-to-nature forest stands using terrestrial mobile laser scanning

Popis výsledku v původním jazyce

In this work, we evaluated mobile laser scanning (MLS) technology for the acquisition of individual tree data in a close-to-natural forest structure. The data was collected during the leaf-on period in a single-tree selection forest stand. Individual tree positions and diameters at breast height (DBHs) were acquired in an automatic process. MLS data was collected on 1000 m2 circular inventory plots. We compared three trajectories consisting of the plot perimeter and 1), two perpendicular lines, 2) an additional concentric circle, and 3) four parallel lines. We compared two algorithms for tree segmentation: 1) a density-based approach and 2) a modified mean-shift al-gorithm. The diameters were estimated using a modified random sample consensus (RANSAC) algorithm. We tested a series of intensity thresholds for filtering returns from green vegetation. We achieved the best results with an intensity threshold of 0,7 quantile of point intensities, and mean-shift segmentation, resulting in the correct ident

Název v anglickém jazyce

Inventory of close-to-nature forest stands using terrestrial mobile laser scanning

Popis výsledku anglicky

In this work, we evaluated mobile laser scanning (MLS) technology for the acquisition of individual tree data in a close-to-natural forest structure. The data was collected during the leaf-on period in a single-tree selection forest stand. Individual tree positions and diameters at breast height (DBHs) were acquired in an automatic process. MLS data was collected on 1000 m2 circular inventory plots. We compared three trajectories consisting of the plot perimeter and 1), two perpendicular lines, 2) an additional concentric circle, and 3) four parallel lines. We compared two algorithms for tree segmentation: 1) a density-based approach and 2) a modified mean-shift al-gorithm. The diameters were estimated using a modified random sample consensus (RANSAC) algorithm. We tested a series of intensity thresholds for filtering returns from green vegetation. We achieved the best results with an intensity threshold of 0,7 quantile of point intensities, and mean-shift segmentation, resulting in the correct ident

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

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

International Journal of Applied Earth Observation and Geoinformation

ISSN

1569-8432

e-ISSN

—

Svazek periodika

115

Číslo periodika v rámci svazku

2022

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

000891767300003

EID výsledku v databázi Scopus

2-s2.0-85142141568