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Yield variability prediction by remote sensing sensors with different spatial resolution

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41310%2F17%3A73710" target="_blank" >RIV/60460709:41310/17:73710 - isvavai.cz</a>

  • Alternative codes found

    RIV/00027006:_____/17:00004053

  • Result on the web

    <a href="http://dx.doi.org/10.1515/intag-2016-0046" target="_blank" >http://dx.doi.org/10.1515/intag-2016-0046</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1515/intag-2016-0046" target="_blank" >10.1515/intag-2016-0046</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Yield variability prediction by remote sensing sensors with different spatial resolution

  • Original language description

    Currently remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView 2 satellite data) spatial resolution together with GreenSeeker hand held crop sensor can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView 2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless better results in comparison with crop yield were obtaine

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Agrophysics

  • ISSN

    0236-8722

  • e-ISSN

    2300-8725

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    PL - POLAND

  • Number of pages

    8

  • Pages from-to

    195-202

  • UT code for WoS article

    000402306100006

  • EID of the result in the Scopus database

    2-s2.0-85020404680