Estimating crop yields at the field level using landsat and modis products
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F18%3A43914375" target="_blank" >RIV/62156489:43210/18:43914375 - isvavai.cz</a>
Alternative codes found
RIV/86652079:_____/18:00500045
Result on the web
<a href="https://doi.org/10.11118/actaun201866051141" target="_blank" >https://doi.org/10.11118/actaun201866051141</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/actaun201866051141" target="_blank" >10.11118/actaun201866051141</a>
Alternative languages
Result language
angličtina
Original language name
Estimating crop yields at the field level using landsat and modis products
Original language description
Remote sensing can be used for yield estimation prior to harvest at the field level to provide helpful information for agricultural decision making. This study was undertaken in Polkovice, located at low elevations in the Czech Republic. From 2014 - 2016, two datasets of satellite imagery were used: the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 datasets. Satellite data were compared with yields and other observations at the level of land blocks. Winter oilseed rape, winter wheat and spring barley yield data, representing the crops planted over the analyzed period, were used for comparison. In 2016, a more detailed analysis was conducted. We tested a relationship between remote sensing data and the spatial yield variability measured by a yield monitor from a combine harvester. Correlations varied from approximately r = 0.4 to r = 0.7 with the highest correlation (r = 0.74) between yield and the Green Normalized Difference Vegetation Index collected from a drone. Vegetation indices from both Landsat 8 and the MODIS showed a positive relationship with yields for the compared period. The highest correlation was between yield and the Enhanced Vegetation Index (r = 0.8) while the lowest was between yield and the Normalized Difference Vegetation Index from MODIS (r = 0.1).
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10510 - Climatic research
Result continuities
Project
<a href="/en/project/EF16_019%2F0000797" target="_blank" >EF16_019/0000797: SustES - Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
ISSN
1211-8516
e-ISSN
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Volume of the periodical
66
Issue of the periodical within the volume
5
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
10
Pages from-to
1141-1150
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85056273124