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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

SGEM2021. Informatics, Geoinformatics and Remote Sensing: Conference Proceedings

ISBN

978-619-7603-22-4

ISSN

1314-2704

e-ISSN

—

Počet stran výsledku

8

Strana od-do

615-622

Název nakladatele

STEF92 Technology Ltd.

Místo vydání

Sofie

Místo konání akce

Albena

Datum konání akce

16. 8. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—