Note: This dataset is not yet peer-reviewed.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 …
Note: This dataset is not yet peer-reviewed.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 …
Note: This dataset is not yet peer-reviewed. Please see the GitHub README associated with this model for more information. This image provides a per-pixel score (in [0, 1]) that indicates whether the pixel area is occupied by undisturbed forest in year 2020. These scores are …
Note: This dataset is not yet peer-reviewed.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 …
Note: This dataset is not yet peer-reviewed.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 …
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis collection of datasets provides probability models for identifying the presence of cocoa, palm, and rubber trees, as well as undisturbed forest, at a 10-meter resolution.\u003c/p\u003e\n"],["\u003cp\u003eThe datasets are developed by the Forest Data Partnership and are intended to support biodiversity, conservation, and land use analysis.\u003c/p\u003e\n"],["\u003cp\u003eEach dataset offers per-pixel probability scores, indicating the likelihood of a specific land cover type being present.\u003c/p\u003e\n"],["\u003cp\u003eThese datasets are pre-review and users should refer to the associated GitHub README for detailed information.\u003c/p\u003e\n"]]],["Four datasets provide per-pixel probability estimates for land cover types: cocoa, palm, and rubber trees, all at 10-meter resolution, and forest persistence in 2020 which is scored between 0-1 to indicate undisturbed forest. All datasets are pre-review and have linked GitHub READMEs for further details. The data relates to biodiversity, conservation, crops, and land use and are associated with the forestdatapartnership project.\n"],null,[]]
