UAV-Borne Imagery Can Supplement Airborne Lidar in the Precise Description of Dynamically Changing Shrubland Woody Vegetation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F22%3A91131" target="_blank" >RIV/60460709:41330/22:91131 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2072-4292/14/9/2287" target="_blank" >https://www.mdpi.com/2072-4292/14/9/2287</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/rs14092287" target="_blank" >10.3390/rs14092287</a>

Result language

angličtina

Original language name

UAV-Borne Imagery Can Supplement Airborne Lidar in the Precise Description of Dynamically Changing Shrubland Woody Vegetation

Original language description

Airborne laser scanning (ALS) is increasingly used for detailed vegetation structure mapping, however, there are many local scale applications where it is economically ineffective or unfeasible from the temporal perspective. Unmanned aerial vehicles (UAVs) or airborne imagery (AImg) appear to be promising alternatives, but only a few studies have examined this assumption outside economically exploited areas (forests, orchards, etc.). The main aim of this study was to compare the usability of normalized digital surface models (nDSMs) photogrammetrically derived from UAV borne and airborne imagery to those derived from low and high density ALS scanning for the precise local scale modelling of woody vegetation structures (the number and height of trees or shrubs) across six dynamically changing shrubland sites. The success of the detection of woody plant tops was initially almost 100 for UAV based models, however, deeper analysis revealed that this was due to the fact that omission and commission errors were approximately equal and the real accuracy was approx. 70% for UAV based models compared to 95,8 for the high density ALS model. The percentage mean absolute errors of shrub or tree heights derived from UAV data ranged between 12,2 and 23,7, and AImg height accuracy was relatively lower. Combining UAV borne or AImg based digital surface models (DSM) with ALS based digital terrain models (DTMs) significantly improved the nDSM height accuracy but failed to significantly improve the detection of the number of individual shrubs or trees. The height accuracy and detection success using low or high density ALS did not differ. Therefore, we conclude that UAV borne imagery has the potential to replace custom ALS in specific local scale applications, especially at dynamically changing sites where repeated ALS is costly, and the combination of such data with (albeit outdated and sparse) ALS based digital terrain models can further improve the success of the use of such data.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

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

Name of the periodical

Remote Sensing

ISSN

2072-4292

e-ISSN

2072-4292

Volume of the periodical

14

Issue of the periodical within the volume

9

Country of publishing house

CH - SWITZERLAND

Number of pages

18

Pages from-to

2287-2304

UT code for WoS article

000794455600001

EID of the result in the Scopus database

2-s2.0-85132588403