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Found 3 papers, 1 papers with code
Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data
To evaluate our approach, we release a new annotated dataset of 7. 4 million agricultural parcels in France and Netherlands.
Crop identification using deep learning on LUCAS crop cover photos
The aim of this paper is to select and publish a subset of LUCAS Cover photos for 12 mature major crops across the EU, to deploy, benchmark, and identify the best configuration of Mobile-net for the classification task, to showcase the possibility of using entropy-based metrics for post-processing of results, and finally to show the applications and limitations of the model in a practical and policy relevant context.
From parcel to continental scale -- A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
Finally, the crop areas derived by classification are compared to the subnational (NUTS 2) area statistics reported by Eurostat.
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