Abstract
Models for the forecasting of crop yields using remotely-sensed satellite data are studied intensively worldwide. After reviewing the experience gained by other researchers in this field, we selected procedures which might be suitable for the estimation of corn and wheat yields in Hungary. In order to study the relations between various remotely-sensed spectral data (and their combinations) and the actually measured final yields we investigated archived agricultural and Landsat MSS spectral data for 1984. A linear relation has been sought and found between the yield data for 47 corn and 55 wheat fields in Hajdú-Bihar county and various weighted and summed spectral quantities. Among the vegetation indices derived from satellite data and corrected for atmospheric effects the most promising were the spectral indices sensitive to the green biomass. The latter, summed over a certain period in the growing season, exhibited a regression of 45-86 per cent, depending on the crop and the period of summation. Using the best models we performed regional yield estimation studies on 295 winter wheat and 218 corn fields. Taking half the crop fields used in the study we determined the yield estimation model and used this to estimate the overall crop production for the other half of the fields. The error of overall corn production estimated by this way turn out to be less than 2 per cent. The model developed for winter wheat proved to be sensitive to the wheat variety.