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Organizations: FDRE - Ministry of Agriculture (MoA)

222 datasets found for "queryValue"

  • Africa SoilGrids nutrients - Total Nitrogen (N) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Total Nitrogen (N) content of the soil fine earth fraction in mg/kg (ppm) as measured according to the soil analytical procedure of wet oxidation 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 nutrients - Total Phosphorus (P) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Total Phosphorus (P) content of the soil fine earth fraction in mg/kg (ppm) as measured according to unspecified analytical methods 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...
    Created October 25, 2023 Updated October 25, 2023
  • Africa Soil Profiles Database, version 1.0 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    ISRIC World Soil Information is compiling legacy soil profile data of Sub Saharan Africa, as a project activity of the AfSIS project (Globally integrated Africa Soil Information Service). http://africasoils.net/services/data/soil-databases/ Africa Soil Profiles database, version. 1.0 (April 2012) identifies less than 15700 unique soil profiles inventoried...
    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 - Soil pH x 10 in KCl N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in KCl 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
  • GeoPearl: SOM-content under arable land 250m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Model predictions on SOM-content under arable land (see: Report: https://edepot.wur.nl/556312 ): 'Predictions with a model ensemble at fixed depths of 15, 45, 80 and 120 cm on a 250m grid. Predictions using an ensemble of Random Forests and Gradient Boosting, with covariates from the SoilGrids 2017 model (Hengl et al. 2017) and a spatial cross-validation...
    Created October 25, 2023 Updated October 25, 2023
  • SoilGrids250m 2.0 - Soil pH in H2O aggregated 5000m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in H2O at 6 standard depths (to convert to pH values divide by 10). 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for...
    Created October 25, 2023 Updated October 25, 2023
  • GeoPearl: SOM-content under arable land 1000m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Model predictions on SOM-content under arable land( Report: https://edepot.wur.nl/556312). Predictions with a model ensemble at fixed depths of 15, 45, 80 and 120 cm. Predictions using an ensemble of Random Forests and Gradient Boosting, with covariates from the SoilGrids 2017 model (Hengl et al. 2017) and a spatial cross-validation procedure. The model...
    Created October 25, 2023 Updated April 17, 2024
  • SoilGrids250m 2.0 - Soil pH in H2O aggregated 1000m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in H2O at 6 standard depths (to convert to pH values divide by 10). 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for...
    Created October 25, 2023 Updated October 25, 2023
  • WoSIS snapshot - December 2023 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The World Soil Information Service (WoSIS) provides quality-assessed and standardized soil profile data to support digital soil mapping and environmental applications at broad scale levels. Since the release of the ‘WoSIS snapshot 2019’ many new soil data were shared with us, registered in the ISRIC data repository, and subsequently standardized in...
    Created April 17, 2024 Updated April 17, 2024
  • WoSIS snapshot - July 2016 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The aim of the World Soil Information Service (WoSIS) is to serve quality-assessed, geo-referenced soil data (point, polygon, and grid) to the international community upon their standardisation and harmonisation. So far, the focus has been on developing procedures for legacy point data with special attention to the selection of soil analytical and...
    Created October 25, 2023 Updated December 25, 2023
  • Africa SoilGrids - Soil pH in H2O N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in H2O at 6 standard depths (to convert to pH values divide by 10) predicted using two sets of Africa soil profiles data. Measurement units: NA. 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,...
    Created October 25, 2023 Updated October 25, 2023
  • WISE derived soil properties on a 30 by 30 arc-seconds global grid N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    This harmonized dataset of derived soil properties for the world (WISE30sec) is comprised of a soil-geographical and a soil attribute component. The GIS dataset was created using the soil map unit delineations of the broad scale Harmonised World Soil Database, version 1.21, with minor corrections, overlaid by a climate zones map (Köppen-Geiger) as...
    Created October 25, 2023 Updated October 25, 2023
  • SoilGrids250m 2.0 - Soil pH in H2O N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil pH x 10 in H2O at 6 standard depths (to convert to pH values divide by 10). 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
  • WoSIS snapshot - September 2019 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The World Soil Information Service (WoSIS) provides quality-assessed and standardised soil profile data to support digital soil mapping and environmental applications at broad scale levels. Since the release of the first ‘WoSIS snapshot’, in July 2016, many new soil data were shared with us, registered in the ISRIC data repository, and subsequently...
    Created October 25, 2023 Updated December 25, 2023
  • International Soil Carbon Network (ISCN) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The International Soil Carbon Network (ISCN) is a science-based network that facilitates data sharing, assembles databases, identifies gaps in data coverage, and enables spatially explicit assessments of soil carbon in context of landscape, climate, land use, and biotic variables.
    Created October 25, 2023 Updated October 25, 2023
  • SoilGrids250m 2017-03 - Probability of occurrence of R horizon N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Probability of occurrence of R horizon 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
  • 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 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 - 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
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