Use of remote sensing data for crop monitoring in precision agriculture

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F23%3A43924531" target="_blank" >RIV/62156489:43210/23:43924531 - isvavai.cz</a>

Výsledek na webu

<a href="https://agrofor.ues.rs.ba/data/20231227-05_Suslikova.pdf" target="_blank" >https://agrofor.ues.rs.ba/data/20231227-05_Suslikova.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Use of remote sensing data for crop monitoring in precision agriculture

Popis výsledku v původním jazyce

Precision agriculture is the modern way of farming that uses knowledge of the heterogeneity of soil conditions and crop vigour within the fields for site-specific crop management. In this study, various multispectral remote sensing methods are compared for monitoring of crop development and plant diagnosis. The primary source of information is freely available data from the Sentinel-2 satellite system, which records the earth&apos;s surface in 13 spectral bands, including bands with high sensitivity to vegetation parameters (red-edge). The revisit time is approximately 3-4 days, and the spatial resolution is 10 m (Blue light-B, Green light - G, Red light -R, Near Infrared - NIR) and 20 m per pixel (Red-Edge - RE, Short-wave infrared -SWIR). The results of the assessment of crop condition from the field experiments carried out in 2021-2023 at two sites in the Czech Republic funded by research projects AF-IGA2023-IP-036 and TAČR SS01020309 showed a high level of correlation between vegetation indices calculated from multispectral images and vegetation parameters such as aboveground biomass or nitrogen uptake. The highest values were obtained using red-edge vegetation indices, such as Normalized Difference Red Edge Index (NDRE), Normalized Difference Moisture Index (NDMI), Enhanced Vegetation Index (EVI). Thus, satellite data can be used to prepare the prescription maps for variable rate application of fertilizers or growth regulators. If more detailed data are required, or in case of unavailability of satellite data due to cloud cover, multispectral unmanned imaging by drones is an option. It provides high operative monitoring to obtain RGB and multispectral orthomosaics with an ultra-high spatial resolution of a few cm without influence of cloud occurrence.

Název v anglickém jazyce

Use of remote sensing data for crop monitoring in precision agriculture

Popis výsledku anglicky

Precision agriculture is the modern way of farming that uses knowledge of the heterogeneity of soil conditions and crop vigour within the fields for site-specific crop management. In this study, various multispectral remote sensing methods are compared for monitoring of crop development and plant diagnosis. The primary source of information is freely available data from the Sentinel-2 satellite system, which records the earth&apos;s surface in 13 spectral bands, including bands with high sensitivity to vegetation parameters (red-edge). The revisit time is approximately 3-4 days, and the spatial resolution is 10 m (Blue light-B, Green light - G, Red light -R, Near Infrared - NIR) and 20 m per pixel (Red-Edge - RE, Short-wave infrared -SWIR). The results of the assessment of crop condition from the field experiments carried out in 2021-2023 at two sites in the Czech Republic funded by research projects AF-IGA2023-IP-036 and TAČR SS01020309 showed a high level of correlation between vegetation indices calculated from multispectral images and vegetation parameters such as aboveground biomass or nitrogen uptake. The highest values were obtained using red-edge vegetation indices, such as Normalized Difference Red Edge Index (NDRE), Normalized Difference Moisture Index (NDMI), Enhanced Vegetation Index (EVI). Thus, satellite data can be used to prepare the prescription maps for variable rate application of fertilizers or growth regulators. If more detailed data are required, or in case of unavailability of satellite data due to cloud cover, multispectral unmanned imaging by drones is an option. It provides high operative monitoring to obtain RGB and multispectral orthomosaics with an ultra-high spatial resolution of a few cm without influence of cloud occurrence.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

40101 - Agriculture

Projekt

<a href="/cs/project/SS01020309" target="_blank" >SS01020309: Precizní zemědělství na pozemcích s regulovaným drenážním odtokem jako nástroj pro ochranu vod a zvýšení efektivity rostlinné výroby</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

AGROFOR International Journal

ISSN

2490-3434

e-ISSN

2490-3442

Svazek periodika

8

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

BA - Bosna a Hercegovina

Počet stran výsledku

8

Strana od-do

41-48

Kód UT WoS článku

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EID výsledku v databázi Scopus

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