Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F20%3A82146" target="_blank" >RIV/60460709:41330/20:82146 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21110/20:00341988

Výsledek na webu

<a href="https://www.tandfonline.com/doi/full/10.1080/17538947.2020.1791267" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/17538947.2020.1791267</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/17538947.2020.1791267" target="_blank" >10.1080/17538947.2020.1791267</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds

Popis výsledku v původním jazyce

Most ground filtering algorithms are primarily designed for airborne LiDAR point cloud processing and their successful use in identifying ground points from photogrammetric point clouds remains questionable. We compared six ground filtering algorithms implemented in Metashape, ArcGIS, CloudCompare, LAStools, and PDAL. We used UAV photogrammetry-based (acquired under leaf-off conditions) and airborne LiDAR (leaf-on) point clouds of the same area to: (i) compare accuracy of generated DTMs (ii) evaluate the effect of vegetation density and terrain slope on filtering accuracy and (iii) assess which algorithm parameters have the greatest effect on the filtering accuracy. Our results show that the performance of filtering algorithms was affected by the point cloud type, terrain slope and vegetation cover. The results were generally better for LiDAR (RMSE 0,13-0,19 m) than for photogrammetric (RMSE 0,19-0,23 m) point clouds. The behavior in varying vegetation and terrain conditions was consistent for LiDAR

Název v anglickém jazyce

Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds

Popis výsledku anglicky

Most ground filtering algorithms are primarily designed for airborne LiDAR point cloud processing and their successful use in identifying ground points from photogrammetric point clouds remains questionable. We compared six ground filtering algorithms implemented in Metashape, ArcGIS, CloudCompare, LAStools, and PDAL. We used UAV photogrammetry-based (acquired under leaf-off conditions) and airborne LiDAR (leaf-on) point clouds of the same area to: (i) compare accuracy of generated DTMs (ii) evaluate the effect of vegetation density and terrain slope on filtering accuracy and (iii) assess which algorithm parameters have the greatest effect on the filtering accuracy. Our results show that the performance of filtering algorithms was affected by the point cloud type, terrain slope and vegetation cover. The results were generally better for LiDAR (RMSE 0,13-0,19 m) than for photogrammetric (RMSE 0,19-0,23 m) point clouds. The behavior in varying vegetation and terrain conditions was consistent for LiDAR

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

<a href="/cs/project/GJ17-17156Y" target="_blank" >GJ17-17156Y: Spojení LiDARu a multispektrálních dat z UAV pro posouzení fyziografické diverzity posttěžebních lokalit</a><br>

Návaznosti

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

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

International Journal of Digital Earth

ISSN

1753-8947

e-ISSN

1753-8955

Svazek periodika

13

Číslo periodika v rámci svazku

12

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

23

Strana od-do

1-23

Kód UT WoS článku

000547045900001

EID výsledku v databázi Scopus

2-s2.0-85087831953