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
- Produced by Google for the Forest Data Partnership
- Earth Engine Snippet
-
ee.ImageCollection("projects/forestdatapartnership/assets/rubber/model_2024a")
- Tags
Description
Note: This dataset is not yet peer-reviewed. Please see the GitHub README associated with this model for more information.
This image collection provides per-pixel probability that the underlying area is occupied by rubber trees.
The probability estimates are provided at 10 meter resolution, and have been generated by a machine learning model. This dataset corresponds to 2020 and 2023 output from model 2024a in 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.
Note that this dataset has separate terms of use for commercial users of Earth Engine. Please see “Terms of Use” tab for details.
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 feedback or additional data to improve these layers, please contact https://goo.gle/fdap-data.
Limitations: Model output is limited to selected countries as calendar year composites for 2020 and 2023. Not all regions of the output are represented by training data. Accuracy is reported in aggregate, is based on a notional threshold, 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. Geographic scope: SE Asia (Thailand, Indonesia, Vietnam, Malaysia, Philippines, Hainan Island), Africa (Côte d'Ivoire, Ghana).
Bands
Resolution
10 meters
Bands
| Name | Min | Max | Description |
|---|---|---|---|
probability |
0 | 1 | Probability that the pixel includes rubber 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
Explore with Earth Engine
Code Editor (JavaScript)
Map.setCenter(106.48584, 11.17099, 11); var collection = ee.ImageCollection( 'projects/forestdatapartnership/assets/rubber/model_2024a'); var r2020 = collection.filterDate('2020-01-01', '2020-12-31').mosaic(); Map.addLayer( r2020.selfMask(), {min: 0.5, max: 1, palette: 'white,blue'}, 'rubber 2020'); var r2023 = collection.filterDate('2023-01-01', '2023-12-31').mosaic(); Map.addLayer( r2023.selfMask(), {min: 0.5, max: 1, palette: 'white,green'}, 'rubber 2023');