A climate envelope model for the projection of carbon storage at global scale

This repository hosts data and code presented in the article "A climate envelope model for the projection of carbon storage at global scale". The repository contains a compressed file containing all the code needed to reproduce the methodology that we developed and to analyse its results. We did not upload all the temporary and intermediate data files that are created during the execution of the method. We rather uploaded "milestone" data, i.e. final results or important intermediate ones. This includes the final training dataset (CSV and ESRI Shapefile), model calibration data (CSV), the final trained model (Python pickle file), the global data for prediction (CSV), the final global map of potential aboveground biomass density (AGBD) at present times (raster files at 1km2 and 10km2 resolution), maps depicting regions where climatic conditions are outside of the training range of positive AGBD instances and maps depicting world regions without trees. Files: code.zip : Compressed directory with all the code needed to reproduce the methodology presented in the manuscript. Contains a README file. agbd_climate_training_dataset_spatialkfolds_1000km.zip : the training dataset in Shapefile format. agbd_climate_training_dataset_spatialkfolds_1000km.csv : the training dataset in CSV format. potential_AGBD_Mgha_1km2_contemporary_climate.tif : the predicted global potential AGBD under contemporary climate conditions and at a resolution of 1 squared kilometer. potential_AGBD_Mgha_10km2_contemporary_climate.tif : the predicted global potential AGBD under contemporary climate conditions downsampled at a resolution of 10 squared kilometers. model_calibration_error_estimation.zip : data on the calibration experiments. number_predictors_out_of_range.zip : tiled maps representing the number of climatic predictors outside of the training range before including 0 AGBD instances in the training dataset. tree_absence_map.zip : tiled maps representing world regions without trees. Based on Crowther et al. (2015) (https://elischolar.library.yale.edu/yale_fes_data/1/). potential_agbd_Mgha_climate_envelope.pkl : Calibrated model for the prediction of potential AGBD given bioclimatic conditions. predictors_data_global.zip : Global predictors data to apply the model on.