Palm Probability model 2025a

projects/forestdatapartnership/assets/palm/model_2025a
info

This dataset is part of a Publisher Catalog, and not managed by Google Earth Engine. Contact forestdatapartnership@googlegroups.com for bugs or view more datasets from the Forest Data Partnership Catalog. Learn more about Publisher datasets.

Catalog Owner
Forest Data Partnership
Dataset Availability
2020-01-01T00:00:00Z–2023-12-31T23:59:59Z
Dataset Provider
Earth Engine Snippet
ee.ImageCollection("projects/forestdatapartnership/assets/palm/model_2025a")
Tags
agriculture biodiversity conservation crop eudr forestdatapartnership landuse palm plantation publisher-dataset

Description

Note: This dataset is not yet peer-reviewed. Please see this GitHub README for more information.

This image collection provides estimated per-pixel probability that the underlying area is occupied by the commodity. The probability estimates are provided at 10 meter resolution, and have been generated by a machine learning model. For details, see the technical documentation on the Forest Data Partnership repo on Github.

The primary purpose of this image collection is to support the mission of the Forest Data Partnership which aims to halt and reverse forest loss from commodity production by collaboratively improving global monitoring, supply chain tracking, and restoration.

This dataset currently covers the following countries: Indonesia, Malaysia, Thailand, Nigeria, Colombia, Brazil, Côte d'Ivoire, Ghana, Ecuador, and Honduras.

This community data product is meant to evolve over time, as more data becomes available from the community and the model used to produce the maps continuously improves. If you would like to provide general feedback or additional datasets to improve these layers, please reach out through this form.

Limitations: Model output is limited to selected countries as calendar year composites for 2020 and 2023. Not all regions of the output are well represented by training data. Accuracy is reported in aggregate, and will vary geographically and with user chosen thresholds. Sensor artifacts based on data availability, cross-track nonuniformity, or cloudiness may be visually apparent in output probabilities and result in classification errors at some thresholds.

Note that this dataset has separate terms of use for commercial users of Earth Engine. Please see "Terms of Use" tab for details.

Bands

Pixel Size
10 meters

Bands

Name Min Max Description
probability 0 1

Probability that the pixel includes palm trees for the given year.

Terms of Use

Terms of Use

For non-commercial users of Earth Engine, use of the dataset is subject to CC-BY 4.0 NC license and requires the following attribution: "Produced by Google for the Forest Data Partnership".

For commercial use of the dataset you may request access using this form. Access will be granted or denied on a case-by-case basis. Commercial use of the dataset is subject to the Forest Data Partnership Datasets Commercial Terms of Use.

Contains modified Copernicus Sentinel data [2015-present]. See the Sentinel Data Legal Notice.

Citations

Citations:
  • Forest Data Partnership. 2025. Community models 2025a. Online

Explore with Earth Engine

Code Editor (JavaScript)

Map.setCenter(110, 0, 11);

var collection = ee.ImageCollection(
    'projects/forestdatapartnership/assets/palm/model_2025a');

var p2020 = collection.filterDate('2020-01-01', '2020-12-31').mosaic();
Map.addLayer(
    p2020.selfMask(), {min: 0.5, max: 1, palette: 'white,blue'}, 'palm 2020');

var p2023 = collection.filterDate('2023-01-01', '2023-12-31').mosaic();
Map.addLayer(
    p2023.selfMask(), {min: 0.5, max: 1, palette: 'white,green'}, 'palm 2023');
Open in Code Editor