Global Maps of Aboveground Biomass, Canopy Height and Cover for 2023 at 10 m Resolution from Multi-Sensor Satellite Imagery

This repository contains the global datasets of aboveground biomass, canopy height and cover accompanying the publication: Weber, M.; Beneke, C.; Wheeler, C. Unified Deep Learning Model for Global Prediction of Aboveground Biomass, Canopy Height, and Cover from High-Resolution, Multi-Sensor Satellite Imagery. Remote Sens. 2025, 17, 1594. https://doi.org/10.3390/rs17091594 The dataset consists of GeoTIFF files covering a latitude range from 57° S to 67° N in splits of 3° x 3° per file. Each file contains 6 bands corresponding to the model outputs with the following order: aboveground biomass density (Mg/ha), AGBD canopy height (cm), CH canopy cover (%), CC standard error of AGBD standard error of CH standard error of CC In addition, an alpha band is included indicating the valid pixels. Non-valid pixels are masked based on the following conditions: is water or is urban build up Due to the storage limit on Zenodo, we provide a sub-sample of 9 globally distributed files (48 GB) of the full dataset (5 TB) in this repository. The files have the following naming convention: earthdaily_agbd_{lon}_{lat}-[data, alpha].tifWe provide the full list of files contained in this dataset in filelist.txt. The sub-sample of files contained in this repository are listed in filelist_sample.txt. The full dataset can be retrieved from a public S3 bucket on AWS as a Requester-Pays service. Note that no transfer costs are incurred if downloading to an AWS resource within the same region (us-west-2). For further details on data transfer costs we refer to the AWS documentation. We encourage users to create their own AWS account (if not already existing) and transfer individual files within the same region by: aws s3 cp s3://eda-appsci-open-access/biomass/earthdaily_agbd_{lon}_{lat}-[data, alpha].tif DESTINATION_PATH --request-payer requester or the full dataset by: aws s3 sync s3://eda-appsci-open-access/biomass/ DESTINATION_PATH --request-payer requester For access without an AWS account, please contact the corresponding author (Manuel Weber). Files in this repository: AGBD_CH_CC_sample_2023.zip; archive of 9 globally distributed sample GeoTIFFs filelist_sample.txt; S3 paths of the sample files filelist.txt; S3 paths of the full dataset