|Julkaisu nro / vuosi:||80/2021|| |
|Julkaisusarja:||Luonnonvara- ja biotalouden tutkimus|| |
|Tekijät:||Maria Yli-Heikkilä, Samantha Wittke, Mirva Kokkinen and Anneli Partala
The general objective of this project was to enhance the crop statistics. To this end, we established a pilot case for an automated process for improved crop yield statistics by merging Earth observation (EO) data, the administrative data, agro-meteorological data and historical crop statistics survey data. The significance of the approach is that the previously very laborious data acquisition process from different sources and the processing of multistep modelling is now by design fully automated and can thus reduce spending on professional surveying. The main achievement is that a new artificial intelligence-based crop yield forecasting system can produce pre-harvest yield predictions for four main cereals (oats, barley, wheat, rye).