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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2012, Vol. 9, No. 1, pp. 95-107

Crop Yield Forecasting Regression Models based on MODIS Data

N.N. Kussul 1, A.N. Kravchenko 1, S.V. Skakun 1, T.I. Adamenko 2, A.Yu. Shelestov 3, A.V. Kolotii 1, Yu.A. Gripich 1
1 Space Research Institute NASU-NSAU, 03680 Kyiv, 40 Glushkov Prospekt, build. 4/1
2 Ukrainian Hydrometeorological Center, 01034,Kyiv, 6-V Zolotovoritska str
3 National University of Life and Environment Sciences of Ukraine, 03187 Kyiv, 15 Geroev Oborony str
Information technology for crop yield forecasting model creation is proposed on the base of satellite data and inductive approach. A first order regression model is used with 16-days composite of maximum NDVI for crop mask as a predictor. A crop mask is built automatically using clusterization of an NDVI time series (using k-means or Kohonen maps). It is shown that accuracy of the forecasting model for the entire region is better than for separate districts. The proposed approach can be used not only for winter wheat crop yield forecasting, but also for other crops, in particular spring crops
Keywords: Crop yield forecasting, regression model, crop mask, information technology, MODIS, NDVI, clusterization, Kohonen map
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