Search datasets for "queryValue"

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Tags: Soil science

219 datasets found for "queryValue"

  • Soil Dataset for Pedotransfer Function Development (IGBP-DIS) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    This uniform soil data set for the development of pedotransfer functions was developed at the request of the Global Soil Data Task (GSDT) of the Data and Information System (DIS) of the International Geosphere Biosphere Programme (IGBP). The necessary chemical and physical soil data have been derived from ISRIC's Soil Information System (ISIS) and the...
    Created October 25, 2023 Updated October 25, 2023
  • Soil and Terrain Database (SOTER) for Tunisia N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Soil and Terrain database for Tunisia primary data (version 1.0), at scale 1:1 million (SOTER_Tunisia), was compiled of enhanced soil information within the framework of the FAO's program of Land Degradation Assessment in Drylands (LADA). A SOTER database was compiled based on the digital soil map of Tunisia. The primary soil and terrain data for...
    Created October 25, 2023 Updated October 25, 2023
  • WISE derived soil properties on a 0.5 by 0.5 degree global grid, version 3.0 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    This harmonized, gridded global data set of soil parameter estimates includes files listing: (1) soil parameter estimates for the component soil units of each terrestrial grid cell, in un-binned format, and (2) soil parameter estimates aggregated or binned into a number of predefined classes. The spatial data, with a resolution of ½ by ½ degree, was...
    Created October 25, 2023 Updated October 25, 2023
  • Soil and Terrain Database for Central Africa (SOTERCAF) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Soil and Terrrain database of Central Africa (SOTERCAF, version 1.0) was compiled at scale 1:2 million for the Democratic Republic of Congo and at scale 1:1 million for Rwanda and Burundi. The SOTERCAF compilation has been a joint collaboration of the Soil Science Laboratory of the University of Ghent, Belgium and ISRIC - World Soil Information,...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Extractable Potassium (K) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Potassium (K) 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) . Values M = mean value...
    Created October 25, 2023 Updated October 25, 2023
  • Africa Soil Profiles Database, version 1.2 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Africa Soil Profiles Database, Version 1.2, is compiled by ISRIC - World Soil Information (World Data Center for Soils) as a project activity for the Globally integrated- Africa Soil Information Service (AfSIS) project (www.africasoils.net/data/legacyprofile). It replaces version 1.1. The Africa Soil Profiles Database is a compilation of...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Nutrient clusters based on fuzzy k-means N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Nutrient clusters based on fuzzy k-means of the soil fine earth fraction and spatially predicted 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...
    Created October 25, 2023 Updated April 17, 2024
  • Africa SoilGrids nutrients - Extractable Zinc (Zn) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Zinc (Zn) content of the soil fine earth fraction in mg/100kg (pp100m) as measured according to the soil analytical procedure of Mehlich 3 and spatially predicted for 0-30 cm depth interval at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data from...
    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 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 nutrients - Extractable Iron (Fe) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    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...
    Created October 25, 2023 Updated October 25, 2023
  • Global distribution of soil phosphorus retention potential N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Limited availability of P in soils to crops may be due to deficiency and/or severe P retention. Earlier studies that drew on large soil profile databases have indicated that it is not (yet) feasible to present meaningful values for “plant-available” soil P, obtained according to comparable analytical methods, that may be linked to soil geographical...
    Created October 25, 2023 Updated October 25, 2023
  • Africa Soil Profiles Database, version 1.1 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Africa Soil Profiles Database, Version 1.1, is compiled by ISRIC - World Soil Information (World Data Center for Soils) as a project activity for the Globally integrated- Africa Soil Information Service (AfSIS) project (www.africasoils.net/data/legacyprofile). It replaces version 1.0. The Africa Soil Profiles Database is a compilation of...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Extractable Phosphorus (P) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Phosphorus (P) content of the soil fine earth fraction in mg/100kg (pp100m) as measured according to the soil analytical procedure of Mehlich 3 and spatially predicted for 0-30 cm depth interval at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Extractable Manganese (Mn) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    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...
    Created October 25, 2023 Updated October 25, 2023
  • WISE derived soil properties on a 5 by 5 arc-minutes global grid, version 1.2 N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Version 1.2 of describes a harmonized dataset of derived soil properties for the world. It was created using the soil distribution shown on the 1:5 million scale FAO-Unesco Soil Map of the World (DSMW), rasterised at 5 by 5 arcminutes, and soil property estimates derived from the ISRIC-WISE soil profile database, version 3.1. The dataset considers 19 soil...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Extractable Calcium (Ca) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Calcium (Ca) 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 nutrients - Extractable Magnesium (Mg) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Magnesium (Mg) 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 nutrients - Extractable Boron (B) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Boron (B) content of the soil fine earth fraction in mg/100kg (pp100m) as measured according to the soil analytical procedure of Mehlich 3 and spatially predicted for 0-30 cm depth interval at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data from...
    Created October 25, 2023 Updated October 25, 2023
  • Africa SoilGrids nutrients - Extractable Copper (Cu) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Extractable Sodium Copper (Cu) of the soil fine earth fraction in mg/100kg (pp100m) as measured according to the soil analytical procedure of Mehlich 3 and spatially predicted for 0-30 cm depth interval at 250 m spatial resolution across sub-Saharan Africa using Machine Learning (ensemble between random forest and gradient boosting) using soil data from...
    Created October 25, 2023 Updated October 25, 2023
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