
Sold by: Meta
Open data
|
Deployed on AWS
Version 2 Global and regional Canopy Height Maps (CHMv2). Created using machine learning models on high-resolution worldwide Vantor satellite imagery.
Overview
Version 2 Global and regional Canopy Height Maps (CHMv2). Created using machine learning models on high-resolution worldwide Vantor satellite imagery.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
How can we make this page better?
Tell us how we can improve this page, or report an issue with this product.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Global Canopy Height maps. GeoTIFF files and Geojson files with observation date
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::dataforgood-fb-data/forests/v2/global/dinov3_global_chm_v2_ml3/
- AWS region
- us-east-1
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://dataforgood-fb-data/forests/v2/global/dinov3_global_chm_v2_ml3//
- Description
- Notifications for new Version 2 High Resolution Canopy Height Maps by WRI and Meta data
- Resource type
- SNS topic
- Amazon Resource Name (ARN)
- arn:aws:sns:us-east-1:632571768781:dataforgood-fb-object_created
- AWS region
- us-east-1
Resources
Vendor resources
Support
Contact
Managed By
How to cite
Version 2 High Resolution Canopy Height Maps by WRI and Meta was accessed on DATE from https://registry.opendata.aws/dataforgood-fb-forestsv2 .
Similar products

Global and regional Canopy Height Maps (CHM). Created using machine learning models on high-resolution worldwide Maxar satellite imagery.
![High Resolution Population Density Maps + Demographic Estimates by [...]](https://d1ewbp317vsrbd.cloudfront.net/344c4e20-a280-4355-a624-7a972005334d.png)
Population data for a selection of countries, allocated to 1 arcsecond blocks and provided in a combination of CSV
and Cloud-optimized GeoTIFF files. This refines CIESIN’s Gridded Population of the World
using machine learning models on high-resolution worldwide Maxar satellite imagery. CIESIN population counts aggregated from worldwide census
data are allocated to blocks where imagery appears to contain buildings.

This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.
Read our doc on how to get AWS Credentials to retrieve this data: https://data.nsidc.earthdatacloud.nasa.gov/s3credentialsREADME

THIS DATASET IS CHANGING
Files uploaded from late January 2026 onward will contain changes including:
precision changes
new parameters
changes to existing parameters e.g. adding vertical levels and timesteps
the height_asl_on_pressure_levels parameter will be replaced by geopotential_height_on_pressure_levels
Please check your systems are prepared for these changes.
A numerical weather prediction forecast for the whole globe, with a resolution of approximately 0.09 degrees i.e. 10km (2,560 x 1,920 grid points). The data is available as NetCDF files. It's offered on a free, unsupported basis, so we don't recommend using it for any critical business purposes.
The global deterministic model is a global configuration of the Unified Model, which is the Met Office’s flagship Numerical Weather Prediction model. The model’s initial state is kept close to the real atmosphere using hybrid 4D-Var data assimilation.
The archive contains dat[...]