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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

40101 - Agriculture

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

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

Name of the periodical

Photogrammetry & Remote Sensing

ISSN

13142704

e-ISSN

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Volume of the periodical

21

Issue of the periodical within the volume

2.1

Country of publishing house

BG - BULGARIA

Number of pages

8

Pages from-to

267-274

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85131678830