The comparasion of satellite and unmanned multispectral imaging for estimation of plant nutritional status of cereals

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F21%3A43921795" target="_blank" >RIV/62156489:43210/21:43921795 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.5593/sgem2021/2.1/s10.74" target="_blank" >https://doi.org/10.5593/sgem2021/2.1/s10.74</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/sgem2021/2.1/s10.74" target="_blank" >10.5593/sgem2021/2.1/s10.74</a>

Result language

angličtina

Original language name

The comparasion of satellite and unmanned multispectral imaging for estimation of plant nutritional status of cereals

Original language description

The aim of the study is the evaluation of multispectral imaging by unmanned aerial vehicles (UAV) and free available satellite data (Sentinel - 2) for the diagnosis of the nutritional status of winter wheat. For this purpose, a field trial was established in 2020 (28 ha of winter wheat), both on the fields of farm enterprise ZD Kojčice (Pelhřimov, Czech Republic). The observation of the fields was performed in two vegetation phases important for the application of nitrogen fertilizers to cereals by topdressing (BBCH 31, BBCH 51). Plant samples were taken in both stages in non-random grid to determine the nitrogen content and the total amount of aboveground biomass. Simultaneously an UAV imaging was carried out by using multispectral camera MicaSense Altum mounted on the drone to capture plant reflectance in green, red, red-edge and near-infrared spectral bands. The images prepared in this way were processed in photogrammetric software to create complete orthomosics. From these data and from the average value estimated by zonal statistics from a 2 m buffer zone around each sampling site, a set of vegetation indices (NDVI, NDRE, etc.) was calculated. For comparison, multispectral images from the Sentinel - 2 satellite were selected near to the sampling date to calculate the similar set of vegetation indices as in the UAV, however with lower spatial resolution. Statistical evaluation by correlation and regression analysis showed a strong relationship between the observed crop parameters and vegetation indices from both remote sensing methods. For estimation of nitrogen uptake, the most sensitive correlations were reached by the red-edge vegetation indices (NDRE, NRERI), on the other hand highest sensitivity the amount of aboveground biomass was achieved NDVI and SRI index.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

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

Article name in the collection

SGEM2021. Informatics, Geoinformatics and Remote Sensing: Conference Proceedings

ISBN

978-619-7603-22-4

ISSN

1314-2704

e-ISSN

—

Number of pages

8

Pages from-to

615-622

Publisher name

STEF92 Technology Ltd.

Place of publication

Sofie

Event location

Albena

Event date

Aug 16, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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