Precision orchard management as a specific form of precision agriculture aims at supporting decision makers and farm managers by providing strategies to optimize crop production. Multiple information sources are used. In this thesis, the use of remote sensing images is explored for that purpose. In the past, an orchard was the smallest management scale to deal with it, whereas nowadays it concerns individual trees and leaves. This research explored downscaling methods for satellite images, bridging the gap between the tree patterns and detailed geographical information of trees on the ground. It focused on using both coarse and very high resolution satellite images with the aim of providing meaningful information at different level of scales.