  The French National Institute of Geographical and Forest Information (IGN)
has the mission to document and measure land-cover on French territory and
provides referential geographical datasets, including high-resolution aerial
images and topographic maps. The monitoring of land-cover plays a crucial role
in land management and planning initiatives, which can have significant
socio-economic and environmental impact. Together with remote sensing
technologies, artificial intelligence (IA) promises to become a powerful tool
in determining land-cover and its evolution. IGN is currently exploring the
potential of IA in the production of high-resolution land cover maps. Notably,
deep learning methods are employed to obtain a semantic segmentation of aerial
images. However, territories as large as France imply heterogeneous contexts:
variations in landscapes and image acquisition make it challenging to provide
uniform, reliable and accurate results across all of France. The FLAIR-one
dataset presented is part of the dataset currently used at IGN to establish the
French national reference land cover map "Occupation du sol \`a grande
\'echelle" (OCS- GE).
