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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.
Note: This dataset is not yet peer-reviewed.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 palm.
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. To provide map-based feedback on this
collection, please see our
Collect Earth Online instance
and follow
these instructions.
If you would like to provide general feedback or additional datasets to
improve these layers, please reach out through
this form.
Bands
Pixel Size 10 meters
Bands
Name
Min
Max
Pixel Size
Description
probability
0
1
meters
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".
Note: This dataset is not yet peer-reviewed.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 palm. The probability estimates are provided at 10 meter resolution, and have been generated by a machine learning …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis dataset provides the probability of palm tree presence at a 10-meter resolution, generated by a machine learning model for the years 2020 and 2023.\u003c/p\u003e\n"],["\u003cp\u003eIt is produced by Google for the Forest Data Partnership to support forest loss monitoring and restoration efforts.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available for non-commercial use under the CC-BY 4.0 NC license, with commercial use subject to separate terms and conditions.\u003c/p\u003e\n"],["\u003cp\u003eThe data is considered a community product and is expected to be refined over time as more data becomes available and models improve.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore the dataset and access code examples through Google Earth Engine.\u003c/p\u003e\n"]]],[],null,["**Caution:** This dataset has been superseded by [projects/forestdatapartnership/assets/palm/model_2025a](/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_palm_model_2025a). \ninfo\n\n\nThis dataset is part of a Publisher Catalog, and not managed by Google Earth Engine.\n\nContact forestdatapartnership@googlegroups.com\n\nfor bugs or [view more datasets](https://developers.google.com/earth-engine/datasets/publisher/forestdatapartnership)\nfrom the Forest Data Partnership Catalog. [Learn more about Publisher datasets](/earth-engine/datasets/publisher). \n[](https://forestdatapartnership.org) \n\nCatalog Owner\n: Forest Data Partnership\n\nDataset Availability\n: 2020-01-01T00:00:00Z--2023-12-31T23:59:59Z\n\nDataset Provider\n:\n\n\n [Produced by Google for the Forest Data Partnership](https://www.forestdatapartnership.org/)\n\nTags\n:\n agriculture \n biodiversity \n conservation \n crop \n eudr \n forestdatapartnership \n landuse \n palm \n plantation \npublisher-dataset \n\nDescription \n**Note: This dataset is not yet peer-reviewed. Please see the GitHub\nREADME associated with this model for more information.**\n\nThis image collection provides per-pixel probability that the underlying\narea is occupied by palm.\n\nThe probability estimates are provided at 10 meter resolution, and have\nbeen generated by a machine learning model. This dataset corresponds to\n2020 and 2023 output from model 2024a in the\n[Forest Data Partnership repo](https://github.com/google/forest-data-partnership/tree/main/models/palm)\non Github.\n\nThe primary purpose of this image collection is to support the mission of\nthe [Forest Data Partnership](https://www.forestdatapartnership.org/)\nwhich aims to halt and reverse forest loss from commodity production\nby collaboratively improving global monitoring, supply chain tracking,\nand restoration.\n\n**Note that this dataset has separate terms of use for commercial users of\nEarth Engine. Please see \"Terms of Use\" tab for details.**\n\nThis community data product is meant to evolve over time, as more data\nbecomes available from the community and the model used to produce the\nmaps continuously improves. To provide map-based feedback on this\ncollection, please see our\n[Collect Earth Online instance](https://app.collect.earth/collection?projectId=50862)\nand follow\n[these instructions](https://collect-earth-online-doc.readthedocs.io/en/latest/collection/simplified.html).\n\nIf you would like to provide general feedback or additional datasets to\nimprove these layers, please reach out through\n[this form](https://goo.gle/fdap-data).\n\nBands\n\n\n**Pixel Size**\n\n10 meters\n\n**Bands**\n\n| Name | Min | Max | Description |\n|---------------|-----|-----|--------------------------------------------------------------------|\n| `probability` | 0 | 1 | Probability that the pixel includes palm trees for the given year. |\n\nTerms of Use\n\n**Terms of Use**\n\nFor non-commercial users of Earth Engine, use of the dataset is subject to\nCC-BY 4.0 NC license and requires the following attribution:\n\"Produced by Google for the Forest Data Partnership\".\n\nFor commercial use of the dataset you may request access using\n[this form](https://docs.google.com/forms/d/e/1FAIpQLSe7L3eh6t2JIPqEtAQwXwY7ZmW52v8W5vrIi4QN_XYgTNJZLw/viewform).\nAccess will be granted or denied on a case by case basis. Commercial use\nof the dataset is subject to the [Forest Data Partnership Datasets\nCommercial Terms of Use](https://services.google.com/fh/files/misc/forest_data_partnership_datasets_commerical_terms_of_use.pdf).\n\nContains modified Copernicus Sentinel data \\[2015-present\\].\nSee the [Sentinel Data Legal Notice](https://sentinels.copernicus.eu/documents/247904/690755/Sentinel_Data_Legal_Notice).\n\nCitations \nCitations:\n\n- N. Clinton, et al. A community palm model. 2024. [Online](https://doi.org/10.48550/arXiv.2405.09530)\n\nDOIs\n\n- \u003chttps://doi.org/10.48550/arXiv.2405.09530\u003e\n\nExplore with Earth Engine **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\nCode Editor (JavaScript) \n\n```javascript\nMap.setCenter(110, 0, 11);\n\nvar collection = ee.ImageCollection(\n 'projects/forestdatapartnership/assets/palm/model_2024a');\n\nvar p2020 = collection.filterDate('2020-01-01', '2020-12-31').mosaic();\nMap.addLayer(\n p2020.selfMask(), {min: 0.5, max: 1, palette: 'white,blue'}, 'palm 2020');\n\nvar p2023 = collection.filterDate('2023-01-01', '2023-12-31').mosaic();\nMap.addLayer(\n p2023.selfMask(), {min: 0.5, max: 1, palette: 'white,green'}, 'palm 2023');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/forestdatapartnership/projects_forestdatapartnership_assets_palm_model_2024a) \n[Palm Probability model 2024a \\[deprecated\\]](/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_palm_model_2024a) \nNote: 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 palm. The probability estimates are provided at 10 meter resolution, and have been generated by a machine learning ... \nprojects/forestdatapartnership/assets/palm/model_2024a, agriculture,biodiversity,conservation,crop,eudr,forestdatapartnership,landuse,palm,plantation,publisher-dataset \n2020-01-01T00:00:00Z/2023-12-31T23:59:59Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.48550/arXiv.2405.09530](https://doi.org/https://www.forestdatapartnership.org/)\n- [https://doi.org/10.48550/arXiv.2405.09530](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_palm_model_2024a)"]]
