- |---| | [### Cocoa Probability model 2026a ![](https://developers.google.com/earth-engine/datasets/images/forestdatapartnership/projects_forestdatapartnership_assets_cocoa_model_2026a_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_cocoa_model_2026a) | | 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 ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [alphaearth-derived](https://developers.google.com/earth-engine/datasets/tags/alphaearth-derived) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [eudr](https://developers.google.com/earth-engine/datasets/tags/eudr) | - |---| | [### Coffee Probability model 2026a ![](https://developers.google.com/earth-engine/datasets/images/forestdatapartnership/projects_forestdatapartnership_assets_coffee_model_2026a_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_coffee_model_2026a) | | 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 ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [alphaearth-derived](https://developers.google.com/earth-engine/datasets/tags/alphaearth-derived) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [eudr](https://developers.google.com/earth-engine/datasets/tags/eudr) | - |---| | [### Global Oil Palm Extent and Planting Year (1990-2021) v1.2 ![](https://developers.google.com/earth-engine/datasets/images/BIOPAMA/BIOPAMA_GlobalOilPalm_v1_2_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/BIOPAMA_GlobalOilPalm_v1_2) | | Global oil palm extent for 2016-2021 at 10 m resolution and oil palm planting year from 1990 to 2021 at 30 m resolution. The dataset consists of 609 100x100 km grid tiles covering tropical and subtropical oil-palm-growing regions worldwide, mapping 23.98 Mha of closed-canopy oil ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [global](https://developers.google.com/earth-engine/datasets/tags/global) [landcover](https://developers.google.com/earth-engine/datasets/tags/landcover) | - |---| | [### Palm Probability model 2026a ![](https://developers.google.com/earth-engine/datasets/images/forestdatapartnership/projects_forestdatapartnership_assets_palm_model_2026a_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_palm_model_2026a) | | 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 ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [alphaearth-derived](https://developers.google.com/earth-engine/datasets/tags/alphaearth-derived) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [eudr](https://developers.google.com/earth-engine/datasets/tags/eudr) | - |---| | [### Rubber Probability model 2026a ![](https://developers.google.com/earth-engine/datasets/images/forestdatapartnership/projects_forestdatapartnership_assets_rubber_model_2026a_sample.png)](https://developers.google.com/earth-engine/datasets/catalog/projects_forestdatapartnership_assets_rubber_model_2026a) | | 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 ... | | [agriculture](https://developers.google.com/earth-engine/datasets/tags/agriculture) [alphaearth-derived](https://developers.google.com/earth-engine/datasets/tags/alphaearth-derived) [biodiversity](https://developers.google.com/earth-engine/datasets/tags/biodiversity) [conservation](https://developers.google.com/earth-engine/datasets/tags/conservation) [crop](https://developers.google.com/earth-engine/datasets/tags/crop) [eudr](https://developers.google.com/earth-engine/datasets/tags/eudr) |