UAV for mapping shrubland vegetation: Does fusion of spectral and vertical information derived from a single sensor increase the classification accuracy?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F19%3A79372" target="_blank" >RIV/60460709:41330/19:79372 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/abs/pii/S0303243418305981?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0303243418305981?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jag.2018.10.009" target="_blank" >10.1016/j.jag.2018.10.009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

UAV for mapping shrubland vegetation: Does fusion of spectral and vertical information derived from a single sensor increase the classification accuracy?

Popis výsledku v původním jazyce

High quality data on plant species occurrence count among the essential data sources for ecological research and conservation purposes. Ecologically valuable small grain mosaics of heterogeneous shrub and herbaceous formations however pose a challenging environment for creating such species occurrence maps. Remote sensing can be useful for such purposes, it however faces several challenges, especially the need of ultra high spatial resolution (centimeters) data and distinguishing between plant species or genera. Unmanned aerial vehicles (UAVs) are capable of producing data with sufficient resolution, their use for identification of plant species is however still largely unexplored. A fusion of spectral data with LiDAR derived vertical information can improve the classification accuracy, such a solution is however costly. A cheaper alternative of vertical data acquisition can be represented by the use of the structure from motion photogrammetry (SfM) utilizing the images taken for (multi hyper)spectra

Název v anglickém jazyce

UAV for mapping shrubland vegetation: Does fusion of spectral and vertical information derived from a single sensor increase the classification accuracy?

Popis výsledku anglicky

High quality data on plant species occurrence count among the essential data sources for ecological research and conservation purposes. Ecologically valuable small grain mosaics of heterogeneous shrub and herbaceous formations however pose a challenging environment for creating such species occurrence maps. Remote sensing can be useful for such purposes, it however faces several challenges, especially the need of ultra high spatial resolution (centimeters) data and distinguishing between plant species or genera. Unmanned aerial vehicles (UAVs) are capable of producing data with sufficient resolution, their use for identification of plant species is however still largely unexplored. A fusion of spectral data with LiDAR derived vertical information can improve the classification accuracy, such a solution is however costly. A cheaper alternative of vertical data acquisition can be represented by the use of the structure from motion photogrammetry (SfM) utilizing the images taken for (multi hyper)spectra

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

International Journal of Applied Earth Observation and Geoinformation

ISSN

0303-2434

e-ISSN

0303-2434

Svazek periodika

75

Číslo periodika v rámci svazku

75

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

151-162

Kód UT WoS článku

000452814800013

EID výsledku v databázi Scopus

2-s2.0-85062823060