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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.", "formats": ["WWW:DOWNLOAD-1.0-ftp--download", "OGC:WMS", "WWW:LINK-1.0-http--related", "canonical"], "keywords": ["soil", "Soil Fertility", "soil chemicophysical properties", "nutrients", "manganese", "digital soil mapping", "Soil science", "Africa"], "providers": [{"name": null, "organization": "ISRIC - World Soil Information", "positionName": null, "roles": [{"name": "pointOfContact"}], "contactInfo": {"phone": {"work": null}, "email": {"work": "soilgrids@isric.org"}, "address": {"work": {"deliveryPoint": null, "city": "Wageningen", "administrativeArea": "GLD", "postalCode": null, "country": "Netherlands"}}, "url": {"url": null, "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://files.isric.org/public/af250m_nutrient/af250m_nutrient_mn_m_agg30cm.tif", "name": "Download GeoTIFF at depth 30 cm", "description": null, "type": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://maps.isric.org/mapserv?map=/map/af250m_nutrient.map", "name": "af250m_nutrient_mn_m_agg30cm", "description": null, "type": "OGC:WMS", "rel": "information"}, {"href": "https://isric.org/projects/africa-soilgrids-soil-nutrient-maps-sub-saharan-africa-250-m-resolution", "name": "Project webpage", "description": null, "type": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://link.springer.com/article/10.1007/s10705-017-9870-x", "name": "Scientific paper", "description": null, "type": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://git.wur.nl/isric/soils4africa/s4a-registry/-/tree/main/data.isric.org/6f418905-226b-4c87-b10a-a44511487b53.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "6f418905-226b-4c87-b10a-a44511487b53", "name": "item", "description": "6f418905-226b-4c87-b10a-a44511487b53", "href": "https://africasis.isric.org/cat/collections/metadata:main/items/6f418905-226b-4c87-b10a-a44511487b53"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://africasis.isric.org/cat/collections/metadata:main"}]}, {"id": "9ab49037-8827-456f-b819-8e4c84aa22ca", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-29.7, -34.9], [-29.7, 28.7], [55.4, 28.7], [55.4, -34.9], [-29.7, -34.9]]]}, "time": ["1980-01-01", "2016-12-31"], "properties": {"themes": [{"scheme": "https://lsc-hubs.org/categories/", "concepts": []}, {"scheme": "https://lsc-hubs.org/tags/", "concepts": []}], "updated": "2021-07-14T11:51:59", "type": "dataset", "language": "None", "externalIds": [{"value": "https://data.isric.org/geonetwork/srv/metadata/9ab49037-8827-456f-b819-8e4c84aa22ca/formatters/xml"}], "title": "Africa SoilGrids nutrients - Extractable Phosphorus (P)", "description": "Extractable Phosphorus (P) content of the soil fine earth fraction in mg/100kg (pp100m) as measured according to the soil analytical procedure of Mehlich 3 and spatially predicted for 0-30 cm depth interval at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data from the Africa Soil Profiles database (AfSP) compiled by AfSIS and recent soil data newly collected by AfSIS in partnership with EthioSIS (Ethiopia), GhaSIS (Ghana) and NiSIS (Nigeria as made possible by OCP Africa and IITA), combined with soil data as made available by Wageningen University and Research, IFDC, VitalSigns, University of California and the OneAcreFund. [Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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[Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutri\u00ebnt Cycling in Agroecosystems 109(1): 77-102). 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For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. 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