Data for Thomas et al Remotely sensed canopy structure improves prediction of soil organic carbon in southern Amazonia

LAI_w_meta_data.csv - dataframe of Canopy Structure from hemispherical photos and data taken in the field with coordinates. (output from 1.LAI_Images_to_dataframe.R) cloud_1.laz.las- Airborne Lidar point clouds cliped to 15m radius of point data. combined_metrics_raster.tif - stacked raster of all gridded data. (output from 4.compile_rasters.R) Field_GEDI_plots.csv - data recorded in the field including plot locations. Gedi_2b_dataframe.csv - dataframe of GEDI L2B data. (output from 5.GEDI_via_Chewie.R) GEDI_height_footprints.csv - additional data recorded in the field including plot locations. Jess_Plinio_soil_samples.csv - dataframe of soil sample data. LAI_locations.csv - coordinates of hemispherical photos. LAI_table.csv - dataframe of Canopy Structure Hemispherical photo. (output from 1.LAI_Images_to_dataframe.R) Lidar_metrics.tif - gridded canopy structure data from Airborne Lidar. (output from 3.lidar_analysis.R) soil_meta_table.csv - dataframe of soil sample data with coordinates. (output from 2.soil_prelim_analysis.R) soil_samples_w_complete_metrics.rds - final dataframe combining all datasets for analaysis. (output from 6.create_complete_metric_table.R) SoilGrids.zip - folder containing all gridded datasets from online sources as TIF files. Variable_Meta_Table.csv - MetaTable to describe all variables available for the machine learning stage of analysis. best_LAI.zip - zipped file containing a hemispherical photo for each soil sample location. The codebase used for processing, analysing and visualising these data are archived with Zenodo at https://doi.org/10.5281sup/zenodo.15005407.