Google & Forest Data Partnership | Share feedback and training data

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As a founding member of the Forest Data Partnership, Google is supporting Forest Data Partnership in developing geospatial commodity models & probability maps to help with deforestation risk assessment.

This is a community driven approach, built on data from across the community to continuously improve the open models and probability maps. See our arXiv pre-print about how we used this method for palm.

For the most recent commodity models and maps check out the Forest Data Partnership catalog on Earth Engine and our repo on GitHub.

Get in touch with us through this form if you're interested in:

Getting notified when new commodity models or probability maps are available
Sharing geospatial training datasets (.geojson, .shpfiles, .csv) containing points or polygons indicating presence of following commodities (palm, rubber, coffee, cocoa, wood)
Providing feedback about published commodity models & probability maps - to submit map-based feedback visit our CEO (Collect Earth Online) project and follow instructions here
Sharing your experience and how the Forest Data Partnership probability maps in your organization and how they helped reduce deforestation

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Getting notified when new commodity models or probability maps are available

Sharing geospatial training datasets (.geojson, .shpfiles, .csv) containing points or polygons indicating presence of following commodities (palm, rubber, coffee, cocoa, wood)

Providing feedback about published commodity models & probability maps

Sharing your experience and how the Forest Data Partnership probability maps are used in your organization and how they helped reduce deforestation

Other:

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[Optional] Short description of dataset you're interested in sharing

We're looking for training datasets containing polygons for commodities driving deforestation (palm, rubber, coffee, cocoa, wood) for any regions across the world.

[Optional] If the dataset is hosted publicly, share a link to the dataset

Anything else you’d like to share?

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