Note: This dataset is not yet peer-reviewed.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Note: This dataset is not yet peer-reviewed.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 …
The Farmscapes 2020 dataset provides high-resolution (25cm) probability maps for three key semi-natural features within England's agricultural landscapes: hedgerows, woodland, and stone walls. This dataset was developed in collaboration with the Oxford Leverhulme Centre for Nature Recovery to serve as a baseline for applications including …
Note: This dataset is not yet peer-reviewed.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 …
The dataset is a 10m global industrial and smallholder oil palm map for 2019. It covers areas where oil palm plantations were detected. The classified images are the output of a convolutional neural network based on Sentinel-1 and Sentinel-2 half-year composites. See article for additional …
Natural Forests of the World 2020, provides a global map of natural forest probability for the year 2020 at a 10-meter resolution. It was developed to support initiatives like the European Union's Deforestation Regulation (EUDR) and other efforts for forest conservation and monitoring. The map …
Note: This dataset is not yet peer-reviewed.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 …
The RESOLVE Ecoregions dataset, updated in 2017, offers a depiction of the 846 terrestrial ecoregions that represent our living planet. View the stylized map at https://ecoregions2017.appspot.com/ or in Earth Engine. Ecoregions, in the simplest definition, are ecosystems of regional extent. Specifically, ecoregions represent distinct assemblages …
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 focuses on biodiversity, conservation, and land use, offering insights into various ecosystems and agricultural practices.\u003c/p\u003e\n"],["\u003cp\u003eIt includes global maps of oil palm plantations and terrestrial ecoregions, along with probability models for cocoa, palm, and rubber tree distributions.\u003c/p\u003e\n"],["\u003cp\u003eSeveral datasets provide high-resolution (10m) data, enabling detailed analysis of land cover and potential environmental impacts.\u003c/p\u003e\n"],["\u003cp\u003eSome datasets, particularly those related to cocoa, palm, and rubber tree probabilities, are pre-review and should be interpreted with caution.\u003c/p\u003e\n"],["\u003cp\u003eThe Forest Persistence dataset helps identify undisturbed forest areas, contributing to deforestation monitoring efforts.\u003c/p\u003e\n"]]],["The datasets include a 2019 global map of industrial and smallholder oil palm plantations derived from Sentinel-1 and Sentinel-2 data, and a 2017 depiction of 846 terrestrial ecoregions. Additionally, there are per-pixel probability models at 10-meter resolution for cocoa, palm, and rubber tree occupancy, as well as a 2020 per-pixel score indicating undisturbed forest areas. Each model is associated with GitHub README for additional information.\n"],null,[]]