Mapping Forest Parameters to Model the Mobility of Terrain Vehicles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F24%3A43925927" target="_blank" >RIV/62156489:43410/24:43925927 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3390/f15111882" target="_blank" >https://doi.org/10.3390/f15111882</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/f15111882" target="_blank" >10.3390/f15111882</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mapping Forest Parameters to Model the Mobility of Terrain Vehicles

Popis výsledku v původním jazyce

This study aims to evaluate the feasibility of using non-contact data collection methods-specifically, UAV (unmanned aerial vehicle)-based and terrestrial laser scanning technologies-to assess forest stand passability, which is crucial for military operations. The research was conducted in a mixed forest stand in the Březina military training area, where the position of trees and their DBHs (Diameter Breast Heights) were recorded. The study compared the effectiveness of different methods, including UAV RGB imaging, UAV-LiDAR, and handheld mobile laser scanning (HMLS), in detecting tree positions and estimating DBH. The results indicate that HMLS data provided the highest number of detected trees and the most accurate positioning relative to the reference measurements. UAV-LiDAR showed better tree detection compared to UAV RGB imaging, though both aerial methods struggled with canopy penetration in densely structured forests. The study also found significant variability in DBH estimation, especially in complex forest stands, highlighting the challenges of accurate tree detection in diverse environments. The findings suggest that while current non-contact methods show promise, further refinement and integration of data sources are necessary to improve their applicability for assessing forest passability in military or rescue contexts.

Název v anglickém jazyce

Mapping Forest Parameters to Model the Mobility of Terrain Vehicles

Popis výsledku anglicky

This study aims to evaluate the feasibility of using non-contact data collection methods-specifically, UAV (unmanned aerial vehicle)-based and terrestrial laser scanning technologies-to assess forest stand passability, which is crucial for military operations. The research was conducted in a mixed forest stand in the Březina military training area, where the position of trees and their DBHs (Diameter Breast Heights) were recorded. The study compared the effectiveness of different methods, including UAV RGB imaging, UAV-LiDAR, and handheld mobile laser scanning (HMLS), in detecting tree positions and estimating DBH. The results indicate that HMLS data provided the highest number of detected trees and the most accurate positioning relative to the reference measurements. UAV-LiDAR showed better tree detection compared to UAV RGB imaging, though both aerial methods struggled with canopy penetration in densely structured forests. The study also found significant variability in DBH estimation, especially in complex forest stands, highlighting the challenges of accurate tree detection in diverse environments. The findings suggest that while current non-contact methods show promise, further refinement and integration of data sources are necessary to improve their applicability for assessing forest passability in military or rescue contexts.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40102 - Forestry

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Forests

ISSN

1999-4907

e-ISSN

1999-4907

Svazek periodika

15

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

13

Strana od-do

1882

Kód UT WoS článku

001366919700001

EID výsledku v databázi Scopus

2-s2.0-85210276078