Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F18%3A78165" target="_blank" >RIV/60460709:41320/18:78165 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/86652079:_____/18:00492799 RIV/62156489:43410/18:43913002

Výsledek na webu

<a href="http://dx.doi.org/10.1080/10095020.2017.1416994" target="_blank" >http://dx.doi.org/10.1080/10095020.2017.1416994</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/10095020.2017.1416994" target="_blank" >10.1080/10095020.2017.1416994</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands

Popis výsledku v původním jazyce

The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas. The objectives are: (1) to test the applicability of UAV visible an near-infrared (VNIR) and geometrical data based on Z values of point dense cloud (PDC) raster to separate forest species and dead trees in the study area, (2) to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling, and (3) to explore the possibility of the qualitative classification of spruce health indicators. Analysis based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir, and for identification of dead tree category. Separation between common beech and fir was distinguished by the object-oriented image analysis. NDVI was able to identify the presence of key indicators of spruce health, such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation, while s

Název v anglickém jazyce

Unmanned aerial vehicles (UAV) for assessment of qualitative classification of Norway spruce in temperate forest stands

Popis výsledku anglicky

The study investigates the potential of UAV-based remote sensing technique for monitoring of Norway spruce health condition in the affected forest areas. The objectives are: (1) to test the applicability of UAV visible an near-infrared (VNIR) and geometrical data based on Z values of point dense cloud (PDC) raster to separate forest species and dead trees in the study area, (2) to explore the relationship between UAV VNIR data and individual spruce health indicators from field sampling, and (3) to explore the possibility of the qualitative classification of spruce health indicators. Analysis based on NDVI and PDC raster was successfully applied for separation of spruce and silver fir, and for identification of dead tree category. Separation between common beech and fir was distinguished by the object-oriented image analysis. NDVI was able to identify the presence of key indicators of spruce health, such as mechanical damage on stems and stem resin exudation linked to honey fungus infestation, while s

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

<a href="/cs/project/LO1415" target="_blank" >LO1415: CzechGlobe 2020 - Rozvoj Centra pro studium dopadů globální změny klimatu</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Geo-Spatial Information Science

ISSN

1009-5020

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

12-20

Kód UT WoS článku

000433052500003

EID výsledku v databázi Scopus

2-s2.0-85048046148