Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F20%3A84557" target="_blank" >RIV/60460709:41320/20:84557 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2072-4292/12/22/3722" target="_blank" >https://www.mdpi.com/2072-4292/12/22/3722</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs12223722" target="_blank" >10.3390/rs12223722</a>
Alternative languages
Result language
angličtina
Original language name
Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging
Original language description
Automatic discrimination of tree species and identification of physiological stress imposed on forest trees by biotic factors from unmanned aerial systems (UAS) offers substantial advantages in forest management practices. In this study, we aimed to develop a novel workflow for facilitating tree species classification and the detection of healthy, unhealthy, and dead trees caused by bark beetle infestation using ultra-high resolution 5-band UAS bi-temporal aerial imagery in the Czech Republic. The study is divided into two steps. We initially classified the tree type, either as broadleaf or conifer, and we then classified trees according to the tree type and health status, and subgroups were created to further classify trees (detailed classification). Photogrammetric processed datasets achieved by the use of structure-from-motion (SfM) imaging technique, where resulting digital terrain models (DTMs), digital surface models (DSMs), and orthophotos with a resolution of 0,05 m were utilized as input for
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20705 - Remote sensing
Result continuities
Project
<a href="/en/project/EF16_019%2F0000803" target="_blank" >EF16_019/0000803: Advanced research supporting the forestry and wood-processing sector´s adaptation to global change and the 4th industrial revolution</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Remote Sensing
ISSN
2072-4292
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
22
Country of publishing house
NN -
Number of pages
21
Pages from-to
1-21
UT code for WoS article
000595212100001
EID of the result in the Scopus database
2-s2.0-85096233593