Comparison of using unmanned aerial vehicle and satellite monitoring to assess the condition of winter wheat stand through NDVI vegetation index

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26296080%3A_____%2F21%3AN0000106" target="_blank" >RIV/26296080:_____/21:N0000106 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sgem.org/index.php/elibrary?view=publication&task=show&id=7915" target="_blank" >https://www.sgem.org/index.php/elibrary?view=publication&task=show&id=7915</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/sgem2021/2.1/s10.63" target="_blank" >10.5593/sgem2021/2.1/s10.63</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of using unmanned aerial vehicle and satellite monitoring to assess the condition of winter wheat stand through NDVI vegetation index

Popis výsledku v původním jazyce

The presented paper deals with the issue of assessing the condition of winter wheat (Triticum aestivum L.) stand during its development in the spring period. The field experiment was established in 2020; two plots sized 25 ha and 16 ha were selected with a model plant of winter wheat. In the spring period (BBCH 35 and BBCH 51), both plots were monitored using an unmanned aerial vehicle (UAV) and Sentinel 2 satellites. After the end of the monitoring, spectral analysis of pictures taken was made and a basic NDVI vegetation index was calculated. Subsequently, spectral maps with this vegetation indexes were prepared. In the initial stage of model plant growth (BBCH 35), Unmanned aerial vehicles exhibited a greater sensitivity of measured data and was able to detect local damage to the stands. Differences in the measured data between UAV and Sentinel 2 were decreasing with the increasing amount of Triticum aestivum L. biomass, and in the advanced stage of vegetation (BBCH 51), a moderately strong positive correlation (R > 0.65) was found between the data measured by UAV and Sentinel 2. The measured values showed that satellite images were less accurate in detecting the occurrence of plant biomass at the beginning of growth. On the other hand, they can be more effective than UAV with the increasing plant biomass as satellite technologies can cover a considerably large area of earth surface during a single flight.

Název v anglickém jazyce

Comparison of using unmanned aerial vehicle and satellite monitoring to assess the condition of winter wheat stand through NDVI vegetation index

Popis výsledku anglicky

The presented paper deals with the issue of assessing the condition of winter wheat (Triticum aestivum L.) stand during its development in the spring period. The field experiment was established in 2020; two plots sized 25 ha and 16 ha were selected with a model plant of winter wheat. In the spring period (BBCH 35 and BBCH 51), both plots were monitored using an unmanned aerial vehicle (UAV) and Sentinel 2 satellites. After the end of the monitoring, spectral analysis of pictures taken was made and a basic NDVI vegetation index was calculated. Subsequently, spectral maps with this vegetation indexes were prepared. In the initial stage of model plant growth (BBCH 35), Unmanned aerial vehicles exhibited a greater sensitivity of measured data and was able to detect local damage to the stands. Differences in the measured data between UAV and Sentinel 2 were decreasing with the increasing amount of Triticum aestivum L. biomass, and in the advanced stage of vegetation (BBCH 51), a moderately strong positive correlation (R > 0.65) was found between the data measured by UAV and Sentinel 2. The measured values showed that satellite images were less accurate in detecting the occurrence of plant biomass at the beginning of growth. On the other hand, they can be more effective than UAV with the increasing plant biomass as satellite technologies can cover a considerably large area of earth surface during a single flight.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

40101 - Agriculture

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Photogrammetry & Remote Sensing

ISSN

13142704

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

2.1

Stát vydavatele periodika

BG - Bulharská republika

Počet stran výsledku

8

Strana od-do

267-274

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85131678830