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Results showed 50.3% of the variance explained, and a RMSE and ME of 0.461 g/kg and 0.038 g/kg, respectively.", "keywords": ["digital surface models", "Eastern Plains", "carbon stock", "carbono org\u00e1nico del suelo", "Colombia", "land use mapping", "Latin America and the Caribbean", "soil", "soil organic carbon", "cartograf\u00eda del uso de la tierra", "Orinoco region", "Earth and Environmental Sciences", "digital soil mapping", "Soil and Water Management", "reconocimiento de suelos", "Multifunctional landscapes", "soil surveys"]}, "links": [{"href": "https://doi.org/10.7910/DVN/ZJMJ7K"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/ZJMJ7K", "name": "item", "description": "10.7910/DVN/ZJMJ7K", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/ZJMJ7K"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10029/623539", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:24:38Z", "type": "Journal Article", "created": "2019-06-12", "title": "Mapping Soil Biodiversity in Europe and the Netherlands", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil is fundamental for the functioning of terrestrial ecosystems, but our knowledge about soil organisms and the habitat they provide (shortly: Soil biodiversity) is poorly developed. For instance, the European Atlas of Soil Biodiversity and the Global Soil Biodiversity Atlas contain maps with rather coarse information on soil biodiversity. This paper presents a methodology to map soil biodiversity with limited data and models. Two issues were addressed. First, the lack of consensus to quantify the soil biodiversity function and second, the limited data to represent large areas. For the later issue, we applied a digital soil mapping (DSM) approach at the scale of the Netherlands and Europe. Data of five groups of soil organisms (earthworms, enchytraeids, micro-arthropods, nematodes, and micro-organisms) in the Netherlands were linked to soil habitat predictors (chemical soil attributes) in a regression analysis. High-resolution maps with soil characteristics were then used together with a model for the soil biodiversity function with equal weights for each group of organisms. To predict soil biodiversity at the scale of Europe, data for soil biological (earthworms and bacteria) and chemical (pH, soil organic matter, and nutrient content) attributes were used in a soil biodiversity model. Differential weights were assigned to the soil attributes after consulting a group of scientists. The issue of reducing uncertainty in soil biodiversity modelling and mapping by the use of data from biological soil attributes is discussed. Considering the importance of soil biodiversity to support the delivery of ecosystem services, the ability to create maps illustrating an aggregate measure of soil biodiversity is a key to future environmental policymaking, optimizing land use, and land management decision support taking into account the loss and gains on soil biodiversity.</p></article>", "keywords": ["2. Zero hunger", "Physical geography", "Soil multi-functionality", "soil biodiversity", "04 agricultural and veterinary sciences", "soil functions", "15. 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Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1\uffe2\uff80\uff89m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world\uffe2\uff80\uff99s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.</p", "keywords": ["Carbon sequestration", "550", "Permafrost", "/704/106/47/4113", "Carbon Dynamics in Peatland Ecosystems", "Digital Soil Mapping Techniques", "Oceanography", "01 natural sciences", "Agricultural and Biological Sciences", "Soil", "Soil water", "Carbon fibers", "Climate change", "2. 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Reports, articles, papers, scientific and non-scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \u201cData reused from the BonaRes Data Centre www.bonares.de.\u201d Although every care has been taken in preparing and testing the soil profile data, the author and BonaRes Data Centre cannot guarantee that the data are correct; neither does the author and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. 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Values M = mean value predicted. 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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Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). 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This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/2991645510"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2991645510", "name": "item", "description": "2991645510", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2991645510"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "290d3e5d-e173-4f6b-8831-053b819d75fc", "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]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:25", "type": "Dataset", "language": "eng", "title": "Africa SoilGrids nutrients - Extractable Sodium (Na)", "description": "Extractable Sodium content (Na) of the soil fine earth fraction in mg/kg (ppm) 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). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "OGC:WMS"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["nutrients", "sodium", "digital soil mapping", "Soil science", "Africa"], "contacts": [{"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/public/af250m_nutrient/af250m_nutrient_na_m_agg30cm.tif", "name": "Download GeoTIFF at depth 30 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://maps.isric.org/mapserv?map=/map/af250m_nutrient.map", "name": "af250m_nutrient_na_m_agg30cm", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://isric.org/projects/africa-soilgrids-soil-nutrient-maps-sub-saharan-africa-250-m-resolution", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://link.springer.com/article/10.1007/s10705-017-9870-x", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://maps.isric.org/mapserv?map=/map/af250m_nutrient.map&SERVICE=WMS&VERSION=1.3.0&REQUEST=GetMap&BBOX=-35,-30,29,56&CRS=EPSG:4326&WIDTH=1426&HEIGHT=895&LAYERS=af250m_nutrient_na_m_agg30cm&STYLES=&FORMAT=png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "290d3e5d-e173-4f6b-8831-053b819d75fc", "name": "item", "description": "290d3e5d-e173-4f6b-8831-053b819d75fc", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/290d3e5d-e173-4f6b-8831-053b819d75fc"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1980-01-01T00:00:00Z", "2016-12-31T00:00:00Z"]}}, {"id": "2997494414", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:03Z", "type": "Journal Article", "created": "2019-12-30", "title": "Pedoclimatic zone-based three-dimensional soil organic carbon mapping in China", "description": "Up-to-date maps of soil organic carbon (SOC) concentrations can provide vital information for monitoring global or regional soil C changes and soil quality. In this study, a national soil dataset collected in the 2010 s was applied to produce SOC maps of mainland China at soil depths of 0\u20135 cm, 5\u201315 cm, 15\u201330 cm, 30\u201360 cm, 60\u2013100 cm and 100\u2013200 cm. A stacking ensemble learning framework was utilized to take advantage of the optimal predictions from individual models. A voting-based ensemble learning model (VELM) was proposed with consideration of pedoclimatic zones. In this model, three machine learning models were separately trained for every pedoclimatic zone, and their predictions were selectively merged together. A weighted ensemble learning model (WELM), in which the parameterization considered all zones (i.e., the whole study area) simultaneously, was also trained for comparison. The overall R2 values of these two methods ranged from 0.16 to 0.57 and decreased with depth. Based on the independent validation, the R2 values ranged from 0.41 to 0.57 in the topsoil (0\u20135 cm, 5\u201315 cm and 15\u201330 cm). Overall accuracy metrics implied that the VELM and WELM yielded nearly the same prediction performances. However, model validation in the pedoclimatic zones showed that the VELM obviously outperformed the WELM, with the VELM generally improving the accuracy by 12.6%. Based on the independent validation, we also compared our predictions with other soil map products. Although the spatial patterns were similar, the predicted SOC maps outperformed two other products. The comparison of the two ensemble models should serve as a reminder that if new national or regional soil maps are generated, validation based on pedoclimatic zones or other soil-landscape units may be necessary before applying these maps.", "keywords": ["Digital soil mapping", "13. Climate action", "Ensemble learning", "Machine learning", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "Model comparison", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Song, Xiao-Dong, Wu, Hua-Yong, Ju, Bing, Liu, Feng, Yang, Fei, Li, De-Cheng, Zhao, Yu-Guo, Yang, Jin-Ling, Zhang, Gan-Lin,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/2997494414"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2997494414", "name": "item", "description": "2997494414", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2997494414"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-04-01T00:00:00Z"}}, {"id": "2a7d2fb8-e0db-4a4b-9661-4809865aaccf", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-18.0, -35.0], [-18.0, 37.0], [51.0, 37.0], [51.0, -35.0], [-18.0, -35.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:34", "type": "Dataset", "language": "eng", "title": "Africa SoilGrids - Texture", "description": "Textural class (defined according to USDA system) at 6 depth intervals derived from sand, silt and clay contents predicted using the Africa Soil Profiles Database (AfSP) v1.2. 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. PLoS ONE 10(6)\n\nTexture classes of the USDA system / triangle used in this map:\ncode, name\n1   clay\n2   silty clay\n3   sandy clay\n4   clay loam\n5   silty clayloam\n6   sandy clay loam\n7   loam\n8   silty loam\n9   sandy loam\n10  silt  \n11  loamy sand\n12  sand", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["texture", "digital soil mapping", "Soil science", "Africa"], "contacts": [{"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd1_250m.tif", "name": "Download GeoTIFF at depth 0-5 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd2_250m.tif", "name": "Download GeoTIFF at depth 5-15 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd3_250m.tif", "name": "Download GeoTIFF at depth 15-30 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd4_250m.tif", "name": "Download GeoTIFF at depth 30-60 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd5_250m.tif", "name": "Download GeoTIFF at depth 60-100 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_TEXMHT_T__M_sd6_250m.tif", "name": "Download GeoTIFF at depth 100-200 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/projects/soil-property-maps-africa-250-m-resolution", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0125814", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/afsis250m/texmht.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "2a7d2fb8-e0db-4a4b-9661-4809865aaccf", "name": "item", "description": "2a7d2fb8-e0db-4a4b-9661-4809865aaccf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2a7d2fb8-e0db-4a4b-9661-4809865aaccf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1960-01-01T00:00:00Z", "2015-12-31T00:00:00Z"]}}, {"id": "2ebc3811-2783-4fb6-bb68-e8af47d32fd3", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-180.0, -56.0], [-180.0, 84.0], [180.0, 84.0], [180.0, -56.0], [-180.0, -56.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Global"}], "scheme": "Region"}], "updated": "2021-07-14T11:51:59", "type": "Dataset", "language": "eng", "title": "SoilGrids250m 2017-03 - Bulk density (fine earth)", "description": "Bulk density (fine earth) in kg / cubic-meter at 7 standard depths predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: kg / m3.", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["bulk density", "digital soil mapping", "Soil science", "Global"], "contacts": [{"name": "Bas Kempen", "organization": "ISRIC - World Soil Information", "position": "Soil mapping specialist", "roles": ["Principal investigator"], "phones": [{"value": null}], "emails": [{"value": "bas.kempen@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl1_250m_ll.tif", "name": "Download GeoTIFF at depth 0 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl2_250m_ll.tif", "name": "Download GeoTIFF at depth 5 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl3_250m_ll.tif", "name": "Download GeoTIFF at depth 15 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl4_250m_ll.tif", "name": "Download GeoTIFF at depth 30 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl5_250m_ll.tif", "name": "Download GeoTIFF at depth 60 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl6_250m_ll.tif", "name": "Download GeoTIFF at depth 100 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BLDFIE_M_sl7_250m_ll.tif", "name": "Download GeoTIFF at depth 200 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://doi.org/10.1371/journal.pone.0169748", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://www.isric.org/explore/soilgrids/faq-soilgrids-2017", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/sg250m/4.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "2ebc3811-2783-4fb6-bb68-e8af47d32fd3", "name": "item", "description": "2ebc3811-2783-4fb6-bb68-e8af47d32fd3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2ebc3811-2783-4fb6-bb68-e8af47d32fd3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1950-01-01T00:00:00Z", "2015-12-01T00:00:00Z"]}}, {"id": "3005528129", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:08Z", "type": "Journal Article", "created": "2020-02-06", "title": "Model averaging for mapping topsoil organic carbon in France", "description": "Abstract   The soil organic carbon (SOC) pool is the largest terrestrial carbon (C) pool and is two to three times larger than the C stored in vegetation and the atmosphere. SOC is a crucial component within the C cycle, and an accurate baseline of SOC is required, especially for biogeochemical and earth system modelling. This baseline will allow better monitoring of SOC dynamics due to land use change and climate change. However, current estimates of SOC stock and its spatial distribution have large uncertainties. In this study, we test whether we can improve the accuracy of the three existing SOC maps of France obtained at national (IGCS), continental (LUCAS), and global (SoilGrids) scales using statistical model averaging approaches. Soil data from the French Soil Monitoring Network (RMQS) were used to calibrate and evaluate five model averaging approaches, i.e., Granger-Ramanathan, Bias-corrected Variance Weighted (BC-VW), Bayesian Modelling Averaging, Cubist and Residual-based Cubist. Cross-validation showed that with a calibration size larger than 100 observations, the five model averaging approaches performed better than individual SOC maps. The BC-VW approach performed best and is recommended for model averaging. Our results show that 200 calibration observations were an acceptable calibration strategy for model averaging in France, showing that a fairly small number of spatially stratified observations (sampling density of 1 sample per 2500\u00a0km2) provides sufficient calibration data. We also tested the use of model averaging in data-poor situations by reproducing national SOC maps using various sized subsets of the IGCS dataset for model calibration. The results show that model averaging always performs better than the national SOC map. However, the Modelling Efficiency dropped substantially when the national SOC map was excluded in model averaging. This indicates the necessity of including a national SOC map for model averaging, even if produced with a small dataset (i.e., 200 samples). This study provides a reference for data-poor countries to improve national SOC maps using existing continental and global SOC maps.", "keywords": ["Soil organic carbon", "[SDV]Life Sciences [q-bio]", "cartographie num\u00e9rique des sols", "04 agricultural and veterinary sciences", "cartographie num\u00e9rique du sol", "Data-poor countries", "15. Life on land", "01 natural sciences", "soil sciences", "sciences du sol", "[SDV] Life Sciences [q-bio]", "Digital soil mapping", "Sample size requirement", "13. Climate action", "carbone organique du sol", "Bias-corrected Variance Weighted", "0401 agriculture", " forestry", " and fisheries", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://hal.science/hal-02473703/file/revised%20accepted%20version%20Chen%20et%20al.pdf"}, {"href": "https://doi.org/3005528129"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3005528129", "name": "item", "description": "3005528129", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3005528129"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-01T00:00:00Z"}}, {"id": "3024869357", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:10Z", "type": "Journal Article", "created": "2020-05-15", "title": "Can pedotransfer functions based on environmental variables improve soil total nutrient mapping at a regional scale?", "description": "Abstract   Numerous pedotransfer functions (PTFs) have been developed to predict the soil properties of interest from other soil properties and, less commonly, from environmental variables. However, only a few PTFs have been developed to predict soil nutrients using environmental variables and to extrapolate them to characterize spatial soil variations at a regional scale. In this study, we attempted to develop PTFs for the total nitrogen (TN), total phosphorus (TP) and total potassium (TK) concentrations in three typical pedo-climatic areas of China (Fujian Province, Jiangsu Province and Qilian Mountains) with diverse climate, terrain and soil types. A series of linear PTFs were developed to quantify the effect of terrain and climate on the predictive relations between the soil nutrients and other measured soil properties and environmental variables. In addition, digital soil mapping (DSM) based on the random forest (RF) technique was performed to test the hypothesis that the best-fit PTFs could be extrapolated, based on soil maps and environmental variables, to describe regional soil variations in the soil nutrients. The root mean square errors (RMSEs) of the best-fit PTFs for TN, TP and TK ranged from 0.21 to 0.79 g kg\u22121, 0.20 to 0.58 g kg\u22121, and 3.68 to 5.00 g kg\u22121, respectively. Different RMSEs were produced by DSM, namely 0.37-1.89 g kg\u22121, 0.19\u22120.56 g kg\u22121 and 3.79-4.83 g kg\u22121 for TN, TP and TK, respectively. PTFs provided a sound basis for database compilation if the soil properties were highly correlated. However, the extrapolation of best-fit PTFs to regional scales yielded greater errors than those produced by DSM. The comparison results reveal the limitations of PTFs and suggest that their performance could be improved by using environmental covariates or by fitting data in areas with relatively homogeneous soil landscapes. The DSM techniques may provide satisfactory alternatives to predict soil data at both regional and plot scales.", "keywords": ["Digital soil mapping", "Total phosphorus", "Total potassium", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Total nitrogen", "15. Life on land", "Regression analysis", "01 natural sciences", "6. Clean water", "Random forest", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/3024869357"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20and%20Tillage%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3024869357", "name": "item", "description": "3024869357", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3024869357"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-01T00:00:00Z"}}, {"id": "3046085810", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:11Z", "type": "Journal Article", "created": "2020-08-03", "title": "Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.</p></article>", "keywords": ["13. Climate action", "citizen science", "digital soil mapping", "Sentinel-1", "0401 agriculture", " forestry", " and fisheries", "synthetic aperture radar (SAR)", " soil moisture", "04 agricultural and veterinary sciences", "15. Life on land"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/12/8/2160/pdf"}, {"href": "https://doi.org/3046085810"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3046085810", "name": "item", "description": "3046085810", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3046085810"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-30T00:00:00Z"}}, {"id": "31d3e559-051a-48be-854b-9bcb1b4bc5c3", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-18.0, -35.0], [-18.0, 37.0], [51.0, 37.0], [51.0, -35.0], [-18.0, -35.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}], "scheme": "Region"}], "updated": "2021-07-14T11:51:49", "type": "Dataset", "language": "eng", "title": "Africa SoilGrids - Exchangeable acidity (H+Al)", "description": "Exchangeable acidity (H+Al measured in 1M KCl) in cmolc/kg (fine earth) at 6 standard depths predicted using two sets of Africa soil profiles data. 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. PLoS ONE 10(6)", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["exchangeable acidity", "digital soil mapping", "Soil science", "Africa"], "contacts": [{"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd1_250m.tif", "name": "Download GeoTIFF at depth 0-5 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd2_250m.tif", "name": "Download GeoTIFF at depth 5-15 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd3_250m.tif", "name": "Download GeoTIFF at depth 15-30 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd4_250m.tif", "name": "Download GeoTIFF at depth 30-60 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd5_250m.tif", "name": "Download GeoTIFF at depth 60-100 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://files.isric.org/public/afsis250m/af_EACKCL_T__M_sd6_250m.tif", "name": "Download GeoTIFF at depth 100-200 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/projects/soil-property-maps-africa-250-m-resolution", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0125814", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/afsis250m/eackcl.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "31d3e559-051a-48be-854b-9bcb1b4bc5c3", "name": "item", "description": "31d3e559-051a-48be-854b-9bcb1b4bc5c3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/31d3e559-051a-48be-854b-9bcb1b4bc5c3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1960-01-01T00:00:00Z", "2015-12-31T00:00:00Z"]}}, {"id": "48d2e636-6bda-4fa3-93c0-fb689fcf3340", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-18.0, -35.0], [-18.0, 37.0], [51.0, 37.0], [51.0, -35.0], [-18.0, -35.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}], "scheme": "Region"}], "updated": "2021-07-14T11:51:54", "type": "Dataset", "language": "eng", "title": "Africa SoilGrids - Exchangeable potassium (K+)", "description": "Exchangeable potassium (K+; measured in 1M NH4OAc buffered at pH 7 with part of the data converted from data measured according to Mehlich 3) in cmolc/kg (fine earth) at 2 depth intervals (0-20 cm and 20-50 cm) predicted using two Africa soil profiles datasets. 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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Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). 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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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Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: probability.", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["soil depth", "digital soil mapping", "Soil science", "Global"], "contacts": [{"name": "Bas Kempen", "organization": "ISRIC - World Soil Information", "position": "Soil mapping specialist", "roles": ["Principal investigator"], "phones": [{"value": null}], "emails": [{"value": "bas.kempen@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/soilgrids/former/2017-03-10/data/BDRLOG_M_250m_ll.tif", "name": "Download GeoTIFF at depth", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://doi.org/10.1371/journal.pone.0169748", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://www.isric.org/explore/soilgrids/faq-soilgrids-2017", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/sg250m/2.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "5da0923b-92e4-4732-bc94-3cb1052069b1", "name": "item", "description": "5da0923b-92e4-4732-bc94-3cb1052069b1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/5da0923b-92e4-4732-bc94-3cb1052069b1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1950-01-01T00:00:00Z", "2015-12-01T00:00:00Z"]}}, {"id": "5dad673a-b96b-4b5c-b2f8-6f8dbdcb6cbd", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-18.0, -35.0], [-18.0, 37.0], [51.0, 37.0], [51.0, -35.0], [-18.0, -35.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}], "scheme": "Region"}], "updated": "2021-07-14T11:51:45", "type": "Dataset", "language": "eng", "title": "Africa SoilGrids - Root zone coarse fragments content aggregated at top 30 cm", "description": "Volumetric coarse fragments content (v%) of the soil whole earth, aggregated over rootable depth and the top 30 cm, mapped at 1km resolution", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "OGC:WMS"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["coarse fragments", "root zone", "digital soil mapping", "Soil science", "Africa"], "contacts": [{"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "1000", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/public/gyga/GYGA_Results/gyga_af_agg_30cm_crfvol__m_1km.tif", "name": "Download GeoTIFF at aggregated 30 cm depth", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://maps.isric.org/mapserv?map=/map/gyga.map", "name": "gyga_af_agg_30cm_crfvol__m_1km", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://doi.org/10.1016/j.geoderma.2018.02.046", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://isric.org/projects/afsis-gyga-functional-soil-information-sub-saharan-africa-rz-pawhc-ssa", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://maps.isric.org/mapserv?map=/map/gyga.map&SERVICE=WMS&VERSION=1.3.0&REQUEST=GetMap&BBOX=-35,-24,38,57&CRS=EPSG:4326&WIDTH=1426&HEIGHT=895&LAYERS=gyga_af_agg_30cm_crfvol__m_1km&STYLES=&FORMAT=png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "5dad673a-b96b-4b5c-b2f8-6f8dbdcb6cbd", "name": "item", "description": "5dad673a-b96b-4b5c-b2f8-6f8dbdcb6cbd", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/5dad673a-b96b-4b5c-b2f8-6f8dbdcb6cbd"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1950-01-01T00:00:00Z", "2015-12-01T00:00:00Z"]}}, {"id": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:55Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil organic carbon concentration map for the topsoil of Hungary (2016)", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales.  The data was prepared according to the methodology of SERENA SOC loss cookbook for the territory of Hungary. To compile the soil organic carbon map, soil organic carbon (0-30 cm, year 2016) data of the Hungarian Soil Information and Monitoring System (SIMS) were used, which are not publicly available. The selection of environmental covariates, which are then used to model and map SOC content, was based on the \u2018scorpan\u2019 model: (s) soil properties, (c) climate, (o) organisms, (r) relief, (p) parent material, (a) age and (n) spatial coordinates. The following covariates were used: soil type map of Hungary (P\u00e1sztor et al., 2018); long-term mean annual evapotranspiration, -evaporation, -precipitation, and -temperature (Szentimrey et al., 2007); CORINE Land Cover 2012; EU-DEM and derivatives; Geological map of Hungary (Gyalog & S\u00edkhegyi, 2005). Random forest kriging (RFK, combination of the random forest machine learning algorithm and the kriging technique) was used for the prediction of the SOC concentration.", "keywords": ["EJP SOIL", "Hungary", "soil organic carbon (SOC)", "SERENA project", "digital soil mapping", "SOC loss"], "contacts": [{"organization": "Ben\u0151, Andr\u00e1s, Szatm\u00e1ri, G\u00e1bor, Bakacsi, Zsofia, P\u00e1sztor, L\u00e1szl\u00f3, Szab\u00f3, Brigitta, Kassai, Piroska, Kocsis, Mih\u00e1ly, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, Laborczi, Annam\u00e1ria,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "name": "item", "description": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "50|od______2659::694ff7c599ecdc11f0dd8cd4c4d84634", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-02T16:26:54Z", "type": "Dataset", "title": "SERENA EJPSOIL IT TUS SOC Loss SOC", "description": "The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  The map is the result of applying the SOC loss cookbook developed in SERENA/EJP-Soil. It is based on Tuscany Region SOCdatabase (Gardin et al., 2021). Not freely available (Lamma Consortium). More information and requests to: info@lamma.toscana.it.  Three versions of the map were produced.  In versions v1 and v2, the dataset corresponds to a map of SOC concentrations for the Tuscany Region produced using a geostatistical approach. Ordinary kriging (Chil\u00e8s & Delfiner, 2012) coupled with local geostatistics (LGS) was used to map SOC concentration (%) in the topsoil (0-30 cm) at a regional scale in the Tuscany Region (Italy). The map has a 50 m spatial resolution.  In version v3, a different approach to applying SOC loss cookbook was used. Particularly, Random Forest regression algorithm with numerous spatial covariates was applied for mapping SOC content (%) in the topsoil (0-30 cm) at regional scale in Tuscany Region (Italy). \u00a0The map has a 100 m spatial resolution.", "keywords": ["EJP Soil", "Random Forest", "Italy", "Tuscany", "Soil Organic Carbon (SOC)", "SOC loss", "Topsoil", "SERENA", "Grant n 862695", "Digital Soil Mapping"], "contacts": [{"organization": "Buttafuoco, Gabriele, Gardin, Lorenzo, Lorenzetti, Romina, Medina-Rold\u00e1n, Eduardo, Ungaro, Fabrizio,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::694ff7c599ecdc11f0dd8cd4c4d84634"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::694ff7c599ecdc11f0dd8cd4c4d84634", "name": "item", "description": "50|od______2659::694ff7c599ecdc11f0dd8cd4c4d84634", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::694ff7c599ecdc11f0dd8cd4c4d84634"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-31T00:00:00Z"}}, {"id": "530b194d-5f66-482f-b536-22db24249f91", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[2.75, 49.45], [2.75, 50.85], [6.5, 50.85], [6.5, 49.45], [2.75, 49.45]]]}, "properties": {"themes": [{"concepts": [{"id": "biota"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Nature et environnement"}, {"id": "Sol et sous-sol"}], "scheme": "https://metawal.wallonie.be/thesaurus/theme-geoportail-wallon"}, {"concepts": [{"id": "Sols"}], "scheme": "http://inspire.ec.europa.eu/theme"}, {"concepts": [{"id": "dynamique naturelle"}, {"id": "biologie"}, {"id": "sol"}], "scheme": "http://geonetwork-opensource.org/gemet-theme"}, {"concepts": [{"id": "biologie du sol"}, {"id": "for\u00eat"}, {"id": "cycle du carbone"}, {"id": "d\u00e9terioration du sol"}, {"id": "organisme du sol"}, {"id": "structure du sol"}, {"id": "carbone organique"}, {"id": "d\u00e9gradation du sol"}, {"id": "fertilit\u00e9 du sol"}, {"id": "carbone"}, {"id": "mati\u00e8re organique"}, {"id": "chimie des sols"}, {"id": "sol"}, {"id": "prairie"}, {"id": "carbone organique total"}], "scheme": "http://geonetwork-opensource.org/gemet"}, {"concepts": [{"id": "BDInfraSIG"}, {"id": "Extraction_DIG"}, {"id": "Reporting INSPIRE"}, {"id": "WalOnMap"}, {"id": "Open Data"}, {"id": "PanierTelechargementGeoportailNO"}], "scheme": "https://metawal.wallonie.be/thesaurus/infrasig"}, {"concepts": [{"id": "R\u00e9gional"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "Observation de la terre et environnement"}], "scheme": "http://data.europa.eu/bna/asd487ae75"}, {"concepts": [{"id": "2023/138"}], "scheme": "http://data.europa.eu/r5r/applicableLegislation"}], "rights": "Conditions d'acc\u00e8s et d'utilisation sp\u00e9cifiques", "updated": "2023-06-21T06:18:06.216Z", "type": "Dataset", "created": "2016-12-30", "language": "fre", "title": "CARBIOSOL - Total organic carbon stocks - period 2005-2014", "description": "Cette couche de donn\u00e9es spatialise les stocks de Carbone Organique total (COT) des sols agricoles du territoire wallon.\n\nLa qualit\u00e9 d\u2019un sol peut \u00eatre \u00e9valu\u00e9e gr\u00e2ce \u00e0 l\u2019\u00e9tude de divers param\u00e8tres physiques, chimiques ou biologiques. Le Carbone Organique total des sols (COT), qui constitue plus de 50% de la masse de la mati\u00e8re organique du sol, est reconnu comme ayant la plus grande influence sur leur qualit\u00e9, et est le plus \u00e9tudi\u00e9 actuellement de par son importance comme puits dans le cycle global du carbone.\n\nLa spatialisation des stocks de COT (et des incertitudes associ\u00e9es) apparaissent donc essentielles pour :\n- d\u00e9tecter les tendances de gains ou de pertes en COT. Ce point est \u00e0 mettre en relation avec les r\u00e9centes et futures politiques (europ\u00e9ennes ou globales) en mati\u00e8re de qualit\u00e9 des sols;\n- localiser les zones sensibles (\u00e0 faible niveau de COT) o\u00f9 prioriser la mise en place de pratiques de conservation.\n\nLa cartographie des stocks en Carbone Organique Total des sols sous cultures et en prairies permanentes a \u00e9t\u00e9 cr\u00e9\u00e9e en 2016 par une m\u00e9thode de mod\u00e9lisation spatiale d\u00e9velopp\u00e9e dans le cadre de la convention CARBIOSOL. Le r\u00e9sultat en sortie du mod\u00e8le est une couche raster des stocks de COT (dans les trente premiers centim\u00e8tres du sol) \u00e0 40 m\u00e8tres de r\u00e9solution et spatialement continue sur l'ensemble du territoire agricole wallon. \n\nPour plus de d\u00e9tails sur la constitution des couches cartographiques g\u00e9n\u00e9r\u00e9es dans le cadre du projet CARBIOSOL, veuillez-vous r\u00e9f\u00e9rer \u00e0 la fiche de m\u00e9tadonn\u00e9es documentant la s\u00e9rie de couches de donn\u00e9es.\n\nPour l'\u00e9tude relative aux stocks de COT, les donn\u00e9es utilis\u00e9es en entr\u00e9e du mod\u00e8le sont :\n- des mesures (observations) de stock de carbone organique total du sol en chaque site d'\u00e9chantillonnage du r\u00e9seau de surveillance des sols (RSS) CARBOSOL pour la p\u00e9riode 2005-2014. Le stock de COT est calcul\u00e9 suivant une relation consid\u00e9rant i) la profondeur d'\u00e9chantillonnage (m), ii) la teneur en carbone organique total (COT - %C) dans le sol, iii) la proportion volumique en \u00e9l\u00e9ments grossiers et iv) la densit\u00e9 apparente de l'horizon (kg/cm\u00b3).\n\n- les co-variables environnementales : l'altitude, les temp\u00e9ratures et pr\u00e9cipitations, l'occupation du sol, des param\u00e8tres connus des sols (classe de drainage naturel, fractions granulom\u00e9triques, etc.). Ces facteurs ont une influence potentielle sur les stocks de carbone organique.\n\nLes stocks sont exprim\u00e9s en M\u00e9gagramme de Carbone par hectare (MgC/ha). 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Extractable Iron (Fe)", "description": "Extractable Iron (Fe) content of the soil fine earth fraction in mg/kg (ppm) 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). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "OGC:WMS"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["nutrients", "iron", "digital soil mapping", "Soil science", "Africa"], "contacts": [{"name": "Johan Leenaars", "organization": "ISRIC - World Soil Information", "position": "Senior soil scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "johan.leenaars@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Tom Hengl", "organization": "ISRIC - World Soil Information", "position": "Former staff", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "None"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "distancevalue": "250", "distanceuom": "m"}, "links": [{"href": "https://files.isric.org/public/af250m_nutrient/af250m_nutrient_fe_m_agg30cm.tif", "name": "Download GeoTIFF at depth 30 cm", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://maps.isric.org/mapserv?map=/map/af250m_nutrient.map", "name": "af250m_nutrient_fe_m_agg30cm", "protocol": "OGC:WMS", "rel": "information"}, {"href": "https://isric.org/projects/africa-soilgrids-soil-nutrient-maps-sub-saharan-africa-250-m-resolution", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://link.springer.com/article/10.1007/s10705-017-9870-x", "name": "Scientific paper", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://maps.isric.org/mapserv?map=/map/af250m_nutrient.map&SERVICE=WMS&VERSION=1.3.0&REQUEST=GetMap&BBOX=-35,-30,29,56&CRS=EPSG:4326&WIDTH=1426&HEIGHT=895&LAYERS=af250m_nutrient_fe_m_agg30cm&STYLES=&FORMAT=png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "5cd5336c-2f45-4430-a9a8-312aa2095cb6", "name": "item", "description": "5cd5336c-2f45-4430-a9a8-312aa2095cb6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/5cd5336c-2f45-4430-a9a8-312aa2095cb6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1980-01-01T00:00:00Z", "2016-12-31T00:00:00Z"]}}, {"id": "62180757-5fed-464c-a450-a05757d02864", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[2.75, 49.45], [2.75, 50.85], [6.5, 50.85], [6.5, 49.45], [2.75, 49.45]]]}, "properties": {"themes": [{"concepts": [{"id": "biota"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Sol et sous-sol"}, {"id": "Nature et environnement"}, {"id": "Agriculture"}], "scheme": "https://metawal.wallonie.be/thesaurus/theme-geoportail-wallon"}, {"concepts": [{"id": "biologie"}, {"id": "dynamique naturelle"}, {"id": "sol"}], "scheme": "http://geonetwork-opensource.org/gemet-theme"}, {"concepts": [{"id": "d\u00e9gradation du sol"}, {"id": "structure du sol"}, {"id": "chimie des sols"}, {"id": "fertilit\u00e9 du sol"}, {"id": "d\u00e9terioration du sol"}, {"id": "organisme du sol"}, {"id": "carbone organique"}, {"id": "biologie du sol"}, {"id": "mati\u00e8re organique"}, {"id": "carbone organique total"}, {"id": "for\u00eat"}, {"id": "carbone"}, {"id": "sol"}, {"id": "prairie"}, {"id": "cycle du carbone"}], "scheme": "http://geonetwork-opensource.org/gemet"}, {"concepts": [{"id": "PanierTelechargementGeoportailNO"}, {"id": "Extraction_DIG"}, {"id": "WalOnMapNO"}, {"id": "BDInfraSIG"}, {"id": "Open Data"}, {"id": "Reporting INSPIRE"}], "scheme": "https://metawal.wallonie.be/thesaurus/infrasig"}, {"concepts": [{"id": "Sols"}], "scheme": "http://inspire.ec.europa.eu/theme"}, {"concepts": [{"id": "R\u00e9gional"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "2023/138 - High Value Datasets Regulation"}], "scheme": "http://data.europa.eu/r5r/applicableLegislation"}, {"concepts": [{"id": "Observation de la terre et environnement"}], "scheme": "http://data.europa.eu/bna/asd487ae75"}, {"concepts": [{"id": "Agriculture, p\u00eache, sylviculture et alimentation"}, {"id": "Environnement"}, {"id": "Science et technologie"}], "scheme": "http://publications.europa.eu/resource/authority/data-theme"}], "updated": "2025-02-14T10:37:37.617429Z", "type": "Dataset", "created": "2024-10-30", "language": "fre", "title": "INSPIRE - CARBIOSOL - Uncertainties of Total Organic Carbon Contents - 2015-2019 period in Wallonia (BE)", "description": "Cette couche de donn\u00e9es INSPIRE reprend les incertitudes des teneurs en Carbone Organique Total dans les sols sous cultures et prairies permanentes du territoire wallon dans la p\u00e9riode 2015-2019.\n\nCette donn\u00e9e conforme INSPIRE est issue de la donn\u00e9e source CARBIOSOL - Incertitudes des Teneurs en Carbone organique total - p\u00e9riode 2015-2019.\n\nCette couche de donn\u00e9es reprend les incertitudes (ici coefficient de variation - CV) de mod\u00e9lisation pour les teneurs en Carbone Organique Total (COT) pr\u00e9dites dans les sols sous cultures et prairies du territoire wallon pour la p\u00e9riode 2015-2019. Il s'agit donc d'une mod\u00e9lisation de l'erreur de pr\u00e9diction.\n\nLa pr\u00e9diction est issue de la mod\u00e9lisation teneurs en carbone organique total des sols sous cultures et prairies dans le cadre du projet CARBIOSOL (UCLouvain - ULi\u00e8ge - DGARNE) et sa production par REQUASUD pour la couche de donn\u00e9es 2015-2019. \nPour plus de d\u00e9tails sur la mod\u00e9lisation mise en place dans la cadre de CARBIOSOL, veuillez-vous r\u00e9f\u00e9rer \u00e0 la fiche de m\u00e9tadonn\u00e9es documentant la s\u00e9rie de couches de donn\u00e9es.\n\nPour chaque occupation du sol, un Mod\u00e8le Additif G\u00e9n\u00e9ralis\u00e9 (GAM pour Generalised Additive Model) a \u00e9t\u00e9 ajust\u00e9 sur un jeu de calibration contenant deux tiers des points d'observation concern\u00e9s. Il a ensuite \u00e9t\u00e9 valid\u00e9 sur le tiers restant.\n\nLa mod\u00e9lisation de l'incertitude est une erreur potentielle qui permet une meilleure interpr\u00e9tation des produits cartographiques finaux g\u00e9n\u00e9r\u00e9s par le projet CARBIOSOL. La cartographie des teneurs en Carbone organique total pour la p\u00e9riode 2015-2019 doit donc \u00eatre lue en association avec la carte des incertitudes. Une incertitude importante refl\u00e8te une pr\u00e9diction moins fiable et donc une plus grande pr\u00e9caution dans l'interpr\u00e9tation des valeurs.\n\nLa cartographie des incertitudes de mod\u00e9lisation associ\u00e9es aux teneurs en COT pr\u00e9dites pour la p\u00e9riode 2015-2019 est une couche raster spatialement continue sur les sols sous cultures et prairies et d'une r\u00e9solution de 90 m\u00e8tres. L'incertitude en chaque pixel est exprim\u00e9e en pourcentage relatif de carbone.", "formats": [{"name": "TIFF (.tif"}, {"name": " .tiff)"}, {"name": "WWW:LINK"}, {"name": "OGC:WMS"}, {"name": "atom:feed"}], "keywords": ["Sol et sous-sol", "Nature et environnement", "Agriculture", "biologie", "dynamique naturelle", "sol", "d\u00e9gradation du sol", "structure du sol", "chimie des sols", "fertilit\u00e9 du sol", "d\u00e9terioration du sol", "organisme du sol", "carbone organique", "biologie du sol", "mati\u00e8re organique", "carbone organique total", "for\u00eat", "carbone", "sol", "prairie", "cycle du carbone", "PanierTelechargementGeoportailNO", "Extraction_DIG", "WalOnMapNO", "BDInfraSIG", "Open Data", "Reporting INSPIRE", "Digital Soil Mapping", "carbiosol", "carbosol", "teneur en carbone", "Aardewerk", "horizon de surface", "sol", "COSW", "DTM", "mod\u00e9lisation", "COT", "CO2", "horizon de sol", "Sols", "R\u00e9gional", "2023/138 - High Value Datasets Regulation", "Observation de la terre et environnement", "Agriculture", " p\u00eache", " sylviculture et alimentation", "Environnement", "Science et technologie"], "contacts": [{"name": null, "organization": "Helpdesk carto du SPW (SPW - 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High Value Datasets Regulation"}], "scheme": "http://data.europa.eu/r5r/applicableLegislation"}, {"concepts": [{"id": "Observation de la terre et environnement"}], "scheme": "http://data.europa.eu/bna/asd487ae75"}, {"concepts": [{"id": "Environnement"}, {"id": "Agriculture, p\u00eache, sylviculture et alimentation"}, {"id": "Science et technologie"}], "scheme": "http://publications.europa.eu/resource/authority/data-theme"}], "updated": "2025-08-06T11:16:53.921024Z", "type": "Dataset", "created": "2024-10-30", "language": "fre", "title": "INSPIRE - CARBIOSOL - Uncertainties of Total Organic Carbon Contents - period 2004-2014 in Wallonia (BE)", "description": "Cette couche de donn\u00e9es INSPIRE reprend les incertitudes des teneurs en Carbone Organique Total dans les sols sous cultures et prairies permanentes du territoire wallon dans la p\u00e9riode 2004-2014.\n\nCette donn\u00e9e conforme INSPIRE est issue de la donn\u00e9e source CARBIOSOL - Incertitudes des Teneurs en Carbone organique total - p\u00e9riode 2004-2014.\n\nElle reprend l'incertitude li\u00e9e au calcul des stocks et \u00e0 la mod\u00e9lisation pour les stocks en COT pr\u00e9dits dans les sols sous cultures et prairies du territoire wallon pour la p\u00e9riode 2004-2014. Il s'agit donc d'une mod\u00e9lisation de l'erreur de pr\u00e9diction.\n\nDans le cadre du projet CARBIOSOL (UCL - ULg - DGARNE), une couche de donn\u00e9es raster de 40 m\u00e8tres de r\u00e9solution des stocks en carbone organique total des sols sous cultures et prairies a \u00e9t\u00e9 g\u00e9n\u00e9r\u00e9e par mod\u00e9lisation spatiale. Ce mod\u00e8le a \u00e9t\u00e9 d\u00e9velopp\u00e9 pour chaque type d'occupation du sol d'int\u00e9r\u00eat (cultures et prairies permanentes).\n\nPour chaque occupation du sol, un Mod\u00e8le Additif G\u00e9n\u00e9ralis\u00e9 (GAM pour Generalised Additive Model) a \u00e9t\u00e9 ajust\u00e9 sur un jeu de calibration contenant deux tiers des points d'observation concern\u00e9s. Il a ensuite \u00e9t\u00e9 valid\u00e9 sur le tiers restant.\n\nPour plus de d\u00e9tails sur la mod\u00e9lisation mise en place dans la cadre de CARBIOSOL, veuillez-vous r\u00e9f\u00e9rer \u00e0 la fiche de m\u00e9tadonn\u00e9es documentant la s\u00e9rie de couches de donn\u00e9es. Les incertitudes de pr\u00e9diction pour les stocks sont calcul\u00e9es selon les recommandations du projet GlobalSoilMap (Heuveling, 2014 - cf. g\u00e9n\u00e9alogie).\n\nLa cartographie des incertitudes de mod\u00e9lisation associ\u00e9es aux stocks en COT pr\u00e9dits est une couche raster spatialement continue sur les sols sous cultures et prairies permanentes et d'une r\u00e9solution de 40 m\u00e8tres. L'incertitude en chaque pixel est exprim\u00e9e en pourcentage relatif (% relatif \u00e0 la valeur m\u00e9diane pr\u00e9dite).\n\nLa mod\u00e9lisation de l'erreur de pr\u00e9diction est une erreur potentielle qui permet une meilleure interpr\u00e9tation des produits cartographiques finaux g\u00e9n\u00e9r\u00e9s par le projet CARBIOSOL. La cartographie des stocks en carbone organique total doit donc \u00eatre lue en association avec la carte des incertitudes. Une incertitude importante refl\u00e8te une pr\u00e9diction moins fiable et donc une plus grande pr\u00e9caution dans l'interpr\u00e9tation des valeurs", "formats": [{"name": "TIFF (.tif"}, {"name": " .tiff)"}, {"name": "WWW:LINK"}, {"name": "OGC:WMS"}, {"name": "atom:feed"}], "keywords": ["Sol et sous-sol", "Nature et environnement", "Agriculture", "biologie", "dynamique naturelle", "sol", "d\u00e9gradation du sol", "structure du sol", "chimie des sols", "fertilit\u00e9 du sol", "d\u00e9terioration du sol", "carbone organique", "biologie du sol", "mati\u00e8re organique", "carbone organique total", "cycle du carbone", "for\u00eat", "carbone", "sol", "prairie", "organisme du sol", "Extraction_DIG", "WalOnMapNO", "BDInfraSIG", "Open Data", "PanierTelechargementGeoportailNO", "Reporting INSPIRE", "Digital Soil Mapping", "carbiosol", "carbosol", "teneur en carbone", "Aardewerk", "horizon de surface", "sol", "COSW", "DTM", "mod\u00e9lisation", "COT", "CO2", "horizon de sol", "Sols", "R\u00e9gional", "2023/138 - High Value Datasets Regulation", "Observation de la terre et environnement", "Environnement", "Agriculture", " p\u00eache", " sylviculture et alimentation", "Science et technologie"], "contacts": [{"name": null, "organization": "Helpdesk carto du SPW (SPW - Secr\u00e9tariat g\u00e9n\u00e9ral - SPW Digital - D\u00e9partement Donn\u00e9es transversales - Gestion et valorisation de la donn\u00e9e)", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "helpdesk.carto@spw.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": null, "organization": "Direction de la Protection des Sols (SPW - Agriculture, Ressources naturelles et Environnement - D\u00e9partement du Sol et des D\u00e9chets - Direction de la Protection des Sols)", "position": null, "roles": ["custodian"], "phones": [{"value": null}], "emails": [{"value": "esther.goidts@spw.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": null, "organization": "Service public de Wallonie (SPW)", "position": null, "roles": ["owner"], "phones": [{"value": null}], "emails": [{"value": "helpdesk.carto@spw.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": "https://geoportail.wallonie.be", "protocol": "WWW:LINK", "protocol_url": "", "name": "G\u00e9oportail de la Wallonie", "name_url": "", "description": "G\u00e9oportail de la Wallonie", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": "information"}}]}, {"name": "Caroline Chartin", "organization": "Universit\u00e9 catholique de Louvain - Earth and Life Institute (UCL - ELI)", "position": null, "roles": ["originator"], "phones": [{"value": null}], "emails": [{"value": "caroline.chartin@uclouvain.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": null, "organization": "R\u00e9seau Qualit\u00e9 Sud (REQUASUD ASBL)", "position": null, "roles": ["originator"], "phones": [{"value": null}], "emails": [{"value": "requasud@cra.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "R\u00e9seau Qualit\u00e9 Sud (REQUASUD ASBL);Universit\u00e9 catholique de Louvain - Earth and Life Institute (UCL - ELI)", "roles": ["creator"]}], "title_alternate": "SO.SoilThemeCoverage.COT__CV_TENEURS_2004_2014", "distancevalue": "90", "distanceuom": "m"}, "links": [{"href": "https://geoportail.wallonie.be/walonmap#PANIER=%5B%7B%22serviceId%22%3A%221%22%2C%22visible%22%3Atrue%2C%22url%22%3A%22https%3A%2F%2Fgeoservices.wallonie.be%2Farcgis%2Frest%2Fservices%2FSOL_SOUS_SOL%2FCARBIOSOL%2FMapServer%2F4%22%2C%22label%22%3A%22CARBIOSOL%20-%20Incertitudes%20des%20Teneurs%20en%20Carbone%20organique%20total%20-%20p%C3%A9riode%202015-2019%22%2C%22type%22%3A%22AGS_DYNAMIC%22%2C%22metadataUrl%22%3A%22https%3A%2F%2Fgeodata.wallonie.be%2Fdoc%2F8279ac41-903a-4196-8d5c-8fa836c949ea%22%7D%5D", "name": "Application WalOnMap - Toute la Wallonie \u00e0 la carte", "description": "Application cartographique du Geoportail (WalOnMap) qui permet de d\u00e9couvrir les donn\u00e9es g\u00e9ographiques de la Wallonie.", "protocol": "WWW:LINK", "rel": "browsing"}, {"href": "https://geoservices.wallonie.be/geoserver/inspire_so/ows?service=WMS&version=1.3.0&request=GetCapabilities", "name": "INSPIRE - Sols en Wallonie (BE) - Service de visualisation WMS", "description": "Ce service de visualisation WMS-INSPIRE permet de consulter la s\u00e9rie de couches de donn\u00e9es conforme au th\u00e8me INSPIRE \"Sols\".", "protocol": "OGC:WMS", "rel": "browsing"}, {"href": "https://geoservices.wallonie.be/inspire/atom/SO_Service.xml", "name": "INSPIRE - Sols en Wallonie (BE) - Service de t\u00e9l\u00e9chargement", "description": "Ce service de t\u00e9l\u00e9chargement ATOM Feed permet de t\u00e9l\u00e9charger la s\u00e9rie de couches de donn\u00e9es conforme au th\u00e8me INSPIRE \"Sols\".", "protocol": "atom:feed", "rel": "download"}, {"href": "https://geodata.wallonie.be/dataset/8279ac41-903a-4196-8d5c-8fa836c949ea", "name": "Page de t\u00e9l\u00e9chargement des donn\u00e9es", "description": "Page \u00e0 partir de laquelle vous avez acc\u00e8s au t\u00e9l\u00e9chargement direct de la donn\u00e9e", "protocol": "WWW:LINK", "rel": "download"}, {"href": "https://metawal.wallonie.be/geonetwork/srv/api/records/8279ac41-903a-4196-8d5c-8fa836c949ea/attachments/SO.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "8279ac41-903a-4196-8d5c-8fa836c949ea", "name": "item", "description": "8279ac41-903a-4196-8d5c-8fa836c949ea", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/8279ac41-903a-4196-8d5c-8fa836c949ea"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2004-01-01T00:00:00Z", "2014-01-31T00:00:00Z"]}}, {"id": "ce58c3ed-03d5-43da-b5cf-376e8faf351c", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[2.75, 49.45], [2.75, 50.85], [6.5, 50.85], [6.5, 49.45], [2.75, 49.45]]]}, "properties": {"themes": [{"concepts": [{"id": "biota"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Nature et environnement"}, {"id": "Agriculture"}, {"id": "Sol et sous-sol"}], "scheme": "https://metawal.wallonie.be/thesaurus/theme-geoportail-wallon"}, {"concepts": [{"id": "dynamique naturelle"}, {"id": "sol"}, {"id": "biologie"}], "scheme": "http://geonetwork-opensource.org/gemet-theme"}, {"concepts": [{"id": "conservation du sol"}, {"id": "type de sol"}, {"id": "cartogramme"}, {"id": "qualit\u00e9 du sol"}, {"id": "culture"}, {"id": "mod\u00e9lisation"}, {"id": "surveillance de l'environnement"}, {"id": "donn\u00e9es sur l'\u00e9tat de l'environnement"}, {"id": "organisme du sol"}, {"id": "ressources du sol"}, {"id": "biologie du sol"}, {"id": "carbone organique total"}, {"id": "stockage"}, {"id": "analyse des sols"}, {"id": "station de surveillance"}, {"id": "cartographie"}, {"id": "carbone organique"}, {"id": "sous-sol"}, {"id": "r\u00e9seau de mesure"}, {"id": "mati\u00e8re organique"}, {"id": "cycle du carbone"}, {"id": "prairie"}, {"id": "sol"}, {"id": "carbone"}, {"id": "for\u00eat"}, {"id": "profil du sol"}, {"id": "utilisation du sol"}], "scheme": "http://geonetwork-opensource.org/gemet"}, {"concepts": [{"id": "PanierTelechargementGeoportailNO"}, {"id": "Extraction_DIG"}, {"id": "Reporting INSPIRE"}, {"id": "BDInfraSIG"}, {"id": "WalOnMapNO"}, {"id": "Open Data"}], "scheme": "https://metawal.wallonie.be/thesaurus/infrasig"}, {"concepts": [{"id": "Sols"}], "scheme": "http://inspire.ec.europa.eu/theme"}, {"concepts": [{"id": "R\u00e9gional"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "2023/138 - High Value Datasets Regulation"}], "scheme": "http://data.europa.eu/r5r/applicableLegislation"}, {"concepts": [{"id": "Observation de la terre et environnement"}], "scheme": "http://data.europa.eu/bna/asd487ae75"}, {"concepts": [{"id": "Agriculture, p\u00eache, sylviculture et alimentation"}, {"id": "Environnement"}, {"id": "Science et technologie"}], "scheme": "http://publications.europa.eu/resource/authority/data-theme"}], "updated": "2025-08-06T11:16:29.845973Z", "type": "Dataset", "created": "2024-10-30", "language": "fre", "title": "INSPIRE - CARBIOSOL - Predicted total organic carbon levels - period 1949-1972 in Wallonia (BE)", "description": "Cette couche de donn\u00e9es INSPIRE reprend les teneurs en Carbone Organique Total dans les sols agricoles du territoire wallon pour la p\u00e9riode 1949-1972.\n\nCette donn\u00e9e conforme INSPIRE est issue de la donn\u00e9e source CARBIOSOL - Teneurs pr\u00e9dites en Carbone organique total - p\u00e9riode 1949-1972.\n\nLa qualit\u00e9 d\u2019un sol peut \u00eatre \u00e9valu\u00e9e gr\u00e2ce \u00e0 l\u2019\u00e9tude de divers param\u00e8tres physiques, chimiques ou biologiques. Parmi ces param\u00e8tres, le carbone organique des sols, qui constitue plus de 50% de la masse de la mati\u00e8re organique du sol, est g\u00e9n\u00e9ralement consid\u00e9r\u00e9 comme l'indicateur principal de la qualit\u00e9 des sols, \u00e0 la fois pour ses fonctions agricoles et environnementales.\n\nLa pr\u00e9sente couche de donn\u00e9es constitue la cartographie des teneurs en carbone organique total (COT) historiques pour les sols sous cultures et prairies permanentes en R\u00e9gion wallonne. La p\u00e9riode couverte par cette cartographie s'\u00e9tend de f\u00e9vrier 1949 \u00e0 juillet 1972. La couche a \u00e9t\u00e9 cr\u00e9\u00e9e par m\u00e9thode de mod\u00e9lisation spatiale d\u00e9velopp\u00e9e par l'UCL dans le cadre de la convention CARBIOSOL.\n\nPour plus de d\u00e9tails sur la constitution des couches cartographiques g\u00e9n\u00e9r\u00e9es dans le cadre du projet CARBIOSOL, veuillez-vous r\u00e9f\u00e9rer \u00e0 la fiche de m\u00e9tadonn\u00e9es documentant la s\u00e9rie de couches de donn\u00e9es.\n\nEn chaque pixel, la teneur en carbone organique total (COT) est exprim\u00e9e en gramme de carbone par kilogramme de terre fine s\u00e8che (gC/kg). Le r\u00e9sultat en sortie du mod\u00e8le est une couche raster des teneurs en COT \u00e0 90 m\u00e8tres de r\u00e9solution et spatialement continue sur le territoire agricole wallon.\n\nLes teneurs moyennes en COT pour les sols sous cultures et prairies sur la p\u00e9riode 1949-1972 \u00e9taient de 1.62 gC/kg et 3.26 gC/kg. Sur cette p\u00e9riode, 9% des superficies agricoles pr\u00e9sentaient des teneurs en COT < 1.15 %C et 60% pr\u00e9sentaient des teneurs < 1.5 gC kg-1. En de\u00e7\u00e0 de 1.15 gC/kg, le sol est d\u00e9structur\u00e9.\n\nLes teneurs en COT des sols pour les deux occupations de sols tendent \u00e0 augmenter du nord-ouest au sud-est, de la r\u00e9gion sablo-limoneuse \u00e0 la r\u00e9gion ardennaise, et rebaisser en r\u00e9gion Jurassique. Cette tendance refl\u00e8te les variations de relief et de sols contr\u00f4lant \u00e9galement l\u2019\u00e9volution de l\u2019occupation des sols (de cultures intensives \u00e0 prairies permanentes extensives dominantes), mais \u00e9galement les variations climatiques.", "formats": [{"name": "TIFF (.tif"}, {"name": " .tiff)"}, {"name": "WWW:LINK"}, {"name": "OGC:WMS"}, {"name": "atom:feed"}], "keywords": ["Nature et environnement", "Agriculture", "Sol et sous-sol", "dynamique naturelle", "sol", "biologie", "conservation du sol", "type de sol", "cartogramme", "qualit\u00e9 du sol", "culture", "mod\u00e9lisation", "surveillance de l'environnement", "donn\u00e9es sur l'\u00e9tat de l'environnement", "organisme du sol", "ressources du sol", "biologie du sol", "carbone organique total", "stockage", "analyse des sols", "station de surveillance", "cartographie", "carbone organique", "sous-sol", "r\u00e9seau de mesure", "mati\u00e8re organique", "cycle du carbone", "prairie", "sol", "carbone", "for\u00eat", "profil du sol", "utilisation du sol", "PanierTelechargementGeoportailNO", "Extraction_DIG", "Reporting INSPIRE", "BDInfraSIG", "WalOnMapNO", "Open Data", "COT", "COS", "CARBIOSOL", "CARBOSOL", "RSS", "teneur en carbone", "Aardewerk", "CNSW", "COSW", "REQUASUD", "RMSE", "GAM", "Mod\u00e8le Additif G\u00e9n\u00e9ralis\u00e9", "MAG", "Monte-Carlo", "covariable", "CO2", "Digital Soil Mapping", "DTM", "Erreur", "horizon de sol", "Sols", "R\u00e9gional", "2023/138 - 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Earth and Life Institute (UCL - ELI)", "position": null, "roles": ["originator"], "phones": [{"value": null}], "emails": [{"value": "caroline.chartin@uclouvain.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": null, "organization": "Cellule SIG du SPW ARNE (SPW - Agriculture, Ressources naturelles et Environnement - D\u00e9partement de l'\u00c9tude du milieu naturel et agricole - Direction de la Coordination des Donn\u00e9es)", "position": null, "roles": ["processor"], "phones": [{"value": null}], "emails": [{"value": "sig.dgarne@spw.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": null, "organization": "R\u00e9seau Qualit\u00e9 Sud (REQUASUD ASBL)", "position": null, "roles": ["originator"], "phones": [{"value": null}], "emails": [{"value": "requasud@cra.wallonie.be"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "R\u00e9seau Qualit\u00e9 Sud (REQUASUD ASBL);Universit\u00e9 catholique de Louvain - 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Sols en Wallonie (BE) - Service de visualisation WMS", "protocol": "OGC:WMS", "rel": null}, {"href": "https://geoservices.wallonie.be/inspire/atom/SO_Service.xml", "name": "INSPIRE - Sols en Wallonie (BE) - Service de t\u00e9l\u00e9chargement", "protocol": "atom:feed", "rel": null}, {"href": "https://geodata.wallonie.be/dataset/ce58c3ed-03d5-43da-b5cf-376e8faf351c", "name": "Page de t\u00e9l\u00e9chargement des donn\u00e9es", "description": "Page \u00e0 partir de laquelle vous avez acc\u00e8s au t\u00e9l\u00e9chargement direct de la donn\u00e9e", "protocol": "WWW:LINK", "rel": "download"}, {"href": "https://metawal.wallonie.be/geonetwork/srv/api/records/ce58c3ed-03d5-43da-b5cf-376e8faf351c/attachments/SO.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "ce58c3ed-03d5-43da-b5cf-376e8faf351c", "name": "item", "description": "ce58c3ed-03d5-43da-b5cf-376e8faf351c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ce58c3ed-03d5-43da-b5cf-376e8faf351c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1949-01-01T00:00:00Z", "1972-01-31T00:00:00Z"]}}, {"id": "cfd1c3c5-b285-480f-b60b-3bc407dfc131", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-180.0, -56.0], [-180.0, 84.0], [180.0, 84.0], [180.0, -56.0], [-180.0, -56.0]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Global"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:26", "type": "Dataset", "language": "eng", "title": "SoilGrids250m 2017-03 - 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Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). 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Solonchaks\", 106: \"Haplic Solonchaks\", 107: \"Haplic Solonchaks (Sodic)\", 108: \"Calcic Solonetz\", 109: \"Gleyic Solonetz\", 110: \"Haplic Solonetz\", 111: \"Mollic Solonetz\", 112: \"Luvic Stagnosols\", 113: \"Haplic Umbrisols\", 114: \"Leptic Umbrisols\", 115: \"Calcic Vertisols\", 116: \"Haplic Vertisols\", 117: \"Haplic Vertisols (Eutric)\", 118: \"Mollic Vertisols\"", "formats": [{"name": "GTiff"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["soil classification", "digital soil mapping", "Soil science", "Global"], "contacts": [{"name": "Bas Kempen", "organization": "ISRIC - World Soil Information", "position": "Soil mapping specialist", "roles": ["Principal investigator"], "phones": [{"value": null}], "emails": [{"value": "bas.kempen@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, 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Manganese (Mn)", "description": "Extractable Manganese (Mn) content of the soil fine earth fraction in mg/kg (ppm) 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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