Show simple item record

dc.contributor.authorMezera, Jiří
dc.contributor.authorLukas, Vojtěch
dc.contributor.authorHorniaček, Igor
dc.contributor.authorSmutný, Vladimír
dc.contributor.authorElbl, Jakub
dc.date.accessioned2022-08-18T00:02:17Z
dc.date.available2022-08-18T00:02:17Z
dc.date.issued2022
dc.identifier.issn1424-8220 Sherpa/RoMEO, JCR
dc.identifier.urihttps://repozitar.mendelu.cz/xmlui/handle/20.500.12698/1617
dc.description.abstractThe presented paper deals with the issue of selecting a suitable system for monitoring the winter wheat crop in order to determine its condition as a basis for variable applications of nitrogen fertilizers. In a four-year (2017-2020) field experiment, 1400 ha of winter wheat crop were monitored using the ISARIA on-the-go system and remote sensing using Sentinel-2 multispectral satellite images. The results of spectral measurements of ISARIA vegetation indices (IRMI, IBI) were statistically compared with the values of selected vegetation indices obtained from Sentinel-2 (EVI, GNDVI, NDMI, NDRE, NDVI and NRERI) in order to determine potential hips. Positive correlations were found between the vegetation indices determined by the ISARIA system and indices obtained by multispectral images from Sentinel-2 satellites. The correlations were medium to strong (r = 0.51-0.89). Therefore, it can be stated that both technologies were able to capture a similar trend in the development of vegetation. Furthermore, the influence of climatic conditions on the vegetation indices was analyzed in individual years of the experiment. The values of vegetation indices show significant differences between the individual years. The results of vegetation indices obtained by the analysis of spectral images from Sentinel-2 satellites varied the most. The values of winter wheat yield varied between the individual years. Yield was the highest in 2017 (7.83 t/ha), while the lowest was recorded in 2020 (6.96 t/ha). There was no statistically significant difference between 2018 (7.27 t/ha) and 2019 (7.44 t/ha).en
dc.format19
dc.publisherMDPI AG (Multidisciplinary Digital Publishing Institute-MDPI)
dc.relation.ispartofSensors
dc.relation.urihttps://doi.org/10.3390/s22010019
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectISARIAen
dc.subjectN crop sensoren
dc.subjectNitrogenen
dc.subjectremote sensingen
dc.subjectSentinelen
dc.subjectVariable rate applicationen
dc.titleComparison of Proximal and Remote Sensing for the Diagnosis of Crop Status in Site-Specific Crop Managementen
dc.typeJ_ČLÁNEK
dc.date.updated2022-08-18T00:02:17Z
dc.description.versionOA
local.identifier.doi10.3390/s22010019
local.identifier.scopus2-s2.0-85121433401
local.identifier.wos000750814100001
local.number1
local.volume22
local.identifier.obd43922292
local.identifier.e-issn1424-8220
dc.project.IDAF-IGA2020-IP054
dc.project.IDAF-IGA2021-IP073
dc.project.IDVyužití družicových systémů Landsat a Sentinel-2 jako podklad pro variabilní aplikaci hnojiv
dc.project.IDVyhodnocení postupů tvorby aplikačních map a strategie variabilního přihnojování porostů obilnin dusíkatými hnojivy
dc.identifier.orcidMezera, Jiří 0000-0002-4713-6576
dc.identifier.orcidLukas, Vojtěch 0000-0001-8051-3305
dc.identifier.orcidHorniaček, Igor 0000-0002-8913-4464
dc.identifier.orcidSmutný, Vladimír 0000-0002-9626-7417
dc.identifier.orcidElbl, Jakub 0000-0001-6401-1516
local.contributor.affiliationAF


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

CC BY 4.0
Except where otherwise noted, this item's license is described as CC BY 4.0