CNN Models, metadata and global trait distribution maps

CNN models, metadata and global trait distribution maps.Files included are:la_inception_resnet_v2.hdf5 + la_xception.hdf5 + la_mobilenet_v2.hdf5: trained models for leaf area predictionsgh_inception_resnet_v2.hdf5 + gh_xception.hdf5 + gh_mobilenet_v2.hdf5: trained models for growth height predictionssla_inception_resnet_v2.hdf5 + sla_xception.hdf5 + sla_mobilenet_v2.hdf5: trained models for specific leaf area predictionsnm_inception_resnet_v2.hdf5 + nm_xception.hdf5 + nm_mobilenet_v2.hdf5: trained models for leaf nitrogen content predictionssm_inception_resnet_v2.hdf5 + sm_xception.hdf5 + sm_mobilenet_v2.hdf5: trained models for seed mass predictionsssd_inception_resnet_v2.hdf5 + ssd_xception.hdf5 + ssd_mobilenet_v2.hdf5: trained models for stem specific density predictionsmetadata.csv: 1. minimum and maximum values of training targets used for normalisation of reference values (can be used to reconvert predictions to original scale when applied to equation (1), see Methods)2. minimum and maximum values of bioclimatic variables used for normalisation of auxiliary data (needed to predict trait values from photographs, see equation (1) in Methods).The order of the bioclimatic variables in the .csv-file corresponds to the order of the auxiliary input to the model (see also R-script '7_train_CNN.R', accessible via https://github.com/ChrSchiller/cnn_traits)gtdm_la.tif, gtdm_gh.tif, gtdm_sla.tif, gtdm_nm.tif, gtdm_sm.tif, gtdm_ssd.tif: global trait distribution maps for the six plant functional traitsgtdm_la_quantile_range.tif, gtdm_gh_quantile_range.tif, gtdm_sla_quantile_range.tif, gtdm_nm_quantile_range.tif, gtdm_sm_quantile_range.tif, gtdm_ssd_quantile_range.tif: global trait quantile range maps for the six plant functional traits