Land use predictions on a regular grid at different scales and with easily accessible covariates

We propose in this paper models that allow to predict land use (urban, agriculture, forests, natural grasslands and soil) at the points of the Teruti-Lucas survey from easily accessible covariates. Our approach involves two steps : first we model land use at the Teruti Lucas point level and second, we propose a method to aggregate land use on regular meshes. The model of the first stage provides fine level predictions. The second step aggregates these predictions on the tiles of the mesh comparing several methods. We are considering various regular meshes of the territory to study the prediction quality depending on the resolution. We show that with easily accessible variables we have an acceptable prediction quality at the point level and that the quality of prediction is improved from the very first stage of aggregation.