3D point cloud fusion from UAV and TLS to assess temperate managed forest structures

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F22%3A92880" target="_blank" >RIV/60460709:41320/22:92880 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1569843222001182" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1569843222001182</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jag.2022.102917" target="_blank" >10.1016/j.jag.2022.102917</a>

Jazyk výsledku

angličtina

Název v původním jazyce

3D point cloud fusion from UAV and TLS to assess temperate managed forest structures

Popis výsledku v původním jazyce

Light detection and ranging (LiDAR) technology has become one of the most dominant acquisition methods for modeling forest attributes, such as very accurate tree structure information, which is necessary for qualitative forest management and research activities. In this study, we evaluated the efficacy of standalone unmanned aerial vehicle-laser scanning (UAV-LS) and terrestrial laser scanning (TLS) data to accurately estimate forest tree metrics under differing management types. Furthermore, we combined the UAV-LS and TLS data to test whether fusion can improve the mapping of the three-dimensional (3D) structure of individual trees to favor accurate estimates of tree metrics. We initially calculated the percentage of point density per square meter aboveground in each height class at intervals of 1 m for the UAV-LS, TLS, and fusion datasets. This helped illustrate the vertical point density distribution that reflects the structural complexity between broadleaf and conifer trees. We then used tree-lev

Název v anglickém jazyce

3D point cloud fusion from UAV and TLS to assess temperate managed forest structures

Popis výsledku anglicky

Light detection and ranging (LiDAR) technology has become one of the most dominant acquisition methods for modeling forest attributes, such as very accurate tree structure information, which is necessary for qualitative forest management and research activities. In this study, we evaluated the efficacy of standalone unmanned aerial vehicle-laser scanning (UAV-LS) and terrestrial laser scanning (TLS) data to accurately estimate forest tree metrics under differing management types. Furthermore, we combined the UAV-LS and TLS data to test whether fusion can improve the mapping of the three-dimensional (3D) structure of individual trees to favor accurate estimates of tree metrics. We initially calculated the percentage of point density per square meter aboveground in each height class at intervals of 1 m for the UAV-LS, TLS, and fusion datasets. This helped illustrate the vertical point density distribution that reflects the structural complexity between broadleaf and conifer trees. We then used tree-lev

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

<a href="/cs/project/EF16_019%2F0000803" target="_blank" >EF16_019/0000803: Excelentní Výzkum jako podpora Adaptace lesnictví a dřevařství na globální změnu a 4. průmyslovou revoluci</a><br>

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

112

Číslo periodika v rámci svazku

2022

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

1-12

Kód UT WoS článku

000844283000002

EID výsledku v databázi Scopus

2-s2.0-85134565162