Grup besar tanah USDA yang diprediksi pada 250 m (probabilitas).
Distribusi kelompok besar tanah USDA berdasarkan prediksi machine learning dari kompilasi global profil tanah. Untuk mempelajari lebih lanjut kelompok besar tanah, lihat Illustrated Guide to Soil Taxonomy - NRCS - USDA.
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Tomislav Hengl, & Travis Nauman. (2018). Grup besar tanah USDA yang diprediksi pada 250 m (probabilitas) (Versi v01) [Set data]. Zenodo.
10.5281/zenodo.1476844
Grup besar tanah USDA yang diprediksi pada 250 m (probabilitas). Distribusi kelompok besar tanah USDA berdasarkan prediksi machine learning dari kompilasi global profil tanah. Untuk mempelajari lebih lanjut kelompok besar tanah, lihat Panduan Bergambar tentang Taksonomi Tanah - NRCS - USDA. Langkah-langkah pemrosesan adalah …
[null,null,[],[[["\u003cp\u003eThis dataset provides predicted probabilities of Hapludalfs soil great group at 250m resolution globally (excluding Antarctica) from 1950 to 2018.\u003c/p\u003e\n"],["\u003cp\u003eIt is based on machine learning predictions using a global compilation of soil profiles and is available through the OpenLandMap project.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and visualize the dataset within Google Earth Engine or externally through OpenGeohub.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is licensed under CC-BY-SA-4.0 and is attributed to Hengl and Nauman (2018).\u003c/p\u003e\n"],["\u003cp\u003eDetailed processing steps and further information are available through provided links to GitLab and Disqus forums.\u003c/p\u003e\n"]]],["This dataset provides predicted probabilities of USDA soil great groups, specifically Hapludalfs, at a 250-meter resolution, excluding Antarctica, from 1950 to 2018. The data is derived from machine learning analysis of global soil profiles. Processing details are available via GitLab. Users can access and visualize maps via Earth Engine, using the provided code snippet to explore the `grtgroup` band, which represents predicted probabilities between 0% and 35%. The dataset is available under a CC-BY-SA-4.0 license.\n"],null,["# OpenLandMap Predicted Hapludalfs Probability\n\nDataset Availability\n: 1950-01-01T00:00:00Z--2018-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [EnvirometriX Ltd](https://doi.org/10.5281/zenodo.1476844)\n\nTags\n:\n [envirometrix](/earth-engine/datasets/tags/envirometrix) [opengeohub](/earth-engine/datasets/tags/opengeohub) [openlandmap](/earth-engine/datasets/tags/openlandmap) [soil](/earth-engine/datasets/tags/soil) \n argillic \nhapludalfs \n\n#### Description\n\nPredicted USDA soil great groups at 250 m (probabilities).\n\nDistribution of the USDA soil great groups based on machine learning predictions\nfrom global compilation of soil profiles. To learn more about soil great groups\nplease refer to the [Illustrated Guide to Soil Taxonomy - NRCS - USDA](https://www.nrcs.usda.gov/wps/PA_NRCSConsumption/download/?cid=stelprdb1247203.pdf).\n\n- Processing steps are described in detail [here](https://gitlab.com/openlandmap/global-layers/tree/master/soil)\n- Antarctica is not included.\n\nTo access and visualize maps outside of Earth Engine, use [this page](https://opengeohub.org/about-openlandmap).\n\nIf you discover a bug, artifact or inconsistency in the LandGIS maps\nor if you have a question please use the following channels:\n\n- [Technical issues and questions about the code](https://gitlab.com/openlandmap/global-layers/issues)\n- [General questions and comments](https://disqus.com/home/forums/landgis/)\n\n### Bands\n\n\n**Pixel Size**\n\n250 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|------------|-------|-----|------|------------|----------------------------------|\n| `grtgroup` | % | 0\\* | 35\\* | meters | Predicted Hapludalfs probability |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-SA-4.0](https://spdx.org/licenses/CC-BY-SA-4.0.html)\n\n### Citations\n\nCitations:\n\n- Tomislav Hengl, \\& Travis Nauman. (2018). Predicted USDA soil great groups at 250 m (probabilities) (Version v01) \\[Data set\\]. Zenodo.\n [10.5281/zenodo.1476844](https://doi.org/10.5281/zenodo.1476844)\n\n### DOIs\n\n- \u003chttps://doi.org/10.5281/zenodo.1476844\u003e\n\n### Explore with Earth Engine\n\n| **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\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('OpenLandMap/SOL/SOL_GRTGROUP_USDA-SOILTAX-HAPLUDALFS_P/v01');\n\nvar visualization = {\n bands: ['grtgroup'],\n min: 0.0,\n max: 35.0,\n palette: ['ffffb2', 'fecc5c', 'fd8d3c', 'f03b20', 'bd0026']\n};\n\nMap.centerObject(dataset);\n\nMap.addLayer(dataset, visualization, 'Hapludalfs');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/OpenLandMap/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX-HAPLUDALFS_P_v01) \n[OpenLandMap Predicted Hapludalfs Probability](/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX-HAPLUDALFS_P_v01) \nPredicted USDA soil great groups at 250 m (probabilities). Distribution of the USDA soil great groups based on machine learning predictions from global compilation of soil profiles. To learn more about soil great groups please refer to the Illustrated Guide to Soil Taxonomy - NRCS - USDA. Processing steps are ... \nOpenLandMap/SOL/SOL_GRTGROUP_USDA-SOILTAX-HAPLUDALFS_P/v01, envirometrix,opengeohub,openlandmap,soil \n1950-01-01T00:00:00Z/2018-01-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.5281/zenodo.1476844](https://doi.org/https://doi.org/10.5281/zenodo.1476844)\n- [https://doi.org/10.5281/zenodo.1476844](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX-HAPLUDALFS_P_v01)"]]
