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Articles

Yield estimation and forecasting for winter wheat in Hungary using time series of MODIS data

, , , , &
Pages 3394-3414 | Received 20 Jun 2016, Accepted 09 Feb 2017, Published online: 21 Mar 2017
 

ABSTRACT

Wheat is one of the most important crops in Hungary, which represents approximately 20% of the entire agricultural area of the country, and about 40% of cereals. A robust yield method has been improved for estimating and forecasting wheat yield in Hungary in the period of 2003–2015 using normalized difference vegetation index (NDVI) derived from the data of the Moderate Resolution Imaging Spectroradiometer. Estimation was made at the end of June – it is generally the beginning of harvest of winter wheat in Hungary – while the forecasts were performed 1–7 weeks earlier. General yield unified robust reference index (GYURRI) vegetation index was calculated each year using different curve-fitting methods to the NDVI time series. The correlation between GYURRI and country level yield data gave correlation coefficient (r) of 0.985 for the examined 13 years in the case of estimation. Simulating a quasi-operative yield estimation process, 10 years’ (2006–2015) yield data was estimated. The differences between the estimated and actual yield data provided by the Hungarian Central Statistical Office were less than 5%, the average difference was 2.5%. In the case of forecasting, these average differences calculated approximately 2 and 4 weeks before the beginning of harvest season were 4.5% and 6.8%, respectively. We also tested the yield estimation procedure for smaller areas, for the 19 counties (Nomenclature of Territorial Units for Statistics-3 level) of Hungary. We found that, the relationship between GYURRI and the county level yield data had r of 0.894 for the years 2003–2014, and by simulating the quasi-operative forecast for 2015, the resulting 19 county average yield values differed from the actual yield as much as 8.7% in average.

Acknowledgements

The research has been supported in part by the Hungarian Scientific Research Fund (OTKA PD–111920). The authors wish to thank the IMAPP team at the Space Science and Engineering Center, University of Wisconsin-Madison and the SeaDAS group for developing and kindly providing us the applied software. The authors wish to thank NASA for producing and distributing the MOD13 NDVI data. Earth Observing System Data and Information System (EOSDIS) 2009. Earth Observing System Clearing House (ECHO)/Reverb Version 10.91.5 [online application]. Greenbelt, MD: EOSDIS, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA). URL: https://wist.echo.nasa.gov/api/.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research has been supported in part by the Hungarian Scientific Research Fund (OTKA PD–111920).

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