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Organizations: FDRE - Ministry of Agriculture (MoA) Tags: digital soil mapping

119 datasets found

  • SoilGrids250m 2017-03 - Grade of a sub-soil being acid e.g. having a pH lower... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Grade of a sub-soil being acid e.g. having a pH greater than 5 and low BS 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: grade.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Predicted WRB 2006 subgroup classes N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Predicted WRB 2006 subgroup classes (as integers) 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')
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - Silt content N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Silt content (2-50/63 micro meter) mass fraction in ‰ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Coarse fragments N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Volumetric coarse fragments content (estimated in the field) in v% (m3/100m3) at 6 standard depths 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....
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Absolute depth to bedrock N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Absolute depth to bedrock (in cm) 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: cm.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Silt content (2-50 micro meter) mass fraction N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Silt content (2-50 micro meter) mass fraction in % 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: w%.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - WRB classes and probabilites N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    WRB classes and probabilites. Predictions were derived using a digital soil mapping approach based on Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org. Legend: 0 = Acrisols 1 = Albeluvisols 2 = Alisols 3 = Andosols 4 = Arenosols 5 = Calcisols 6 = Cambisols...
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - Soil organic carbon density N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil organic carbon density in g/dm³ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - Coarse fragments volumetric N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Coarse fragments volumetric in ‱ at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Cation exchange capacity (CEC) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Cation exchange capacity of soil in cmolc/kg 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: cmolc / kg.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Soil pH in H2O N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in H2O at 7 standard depths (to convert to pH values divide by 10) 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: NA.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Predicted probability USDA 2014 suborder classes N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Predicted probability in percent per class 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: probability.
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids nutrients - Extractable Sodium (Na) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    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...
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Texture N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    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....
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Depth to bedrock (R horizon) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Depth to bedrock (R horizon) up to 200 cm 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: cm.
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids nutrients - Extractable Aluminium (Al) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Aluminium (Al) 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...
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Drainage classes N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Drainage classes, defined according to the Guidelines for Soil Description (FAO, 2006) predicted using the Africa Soil Profiles Database (AfSP) v1.2. LEGEND = 1:Very poor, 2:Poor, 3:Imperfect, 4:Moderate, 5:Well, 6:Somewhat excessive, 7:Excessive, 255:NODATA. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B....
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Extractable aluminium (Al) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable aluminium content (Al measured by Mehlich 3) in mg/kg (fine earth) at 2 depth intervals (0-20 cm and 20-50 cm) 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....
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Sand content N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Sand content (50-2000 micro meter) in g/100g (w%) 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...
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Soil organic carbon (SOC) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil organic carbon content (measured by either wet oxidation or dry combustion at 900 C) in g/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...
    Created October 25, 2023 • Updated October 25, 2023
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