A comprehensive methodology was implemented fusing multiple channels (RGB, LiDAR intensity, Infrared, Height, etc.), covering from the labeling system to the classification ingletear process to distinguish tree and non-tree areas. Point clouds from the Spanish Government PNOA project were used. From the LiDAR information a DEM model was created, and from it the image was segmented into similar areas. After, the information of those areas was aggregated using OWA operators. Finally, our method demonstrates that the smart aggregation of diverse data sources can enhance tree classification.