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Organizations: FDRE - Ministry of Agriculture (MoA)

244 datasets found

  • Africa SoilGrids - Exchangeable aluminium (Al3+) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Exchangeable aluminium (Al3+ measured in 1M KCl solution) in cmolc/kg (fine earth) at two 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,...
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Root zone coarse fragments content aggregated at top 30 cm N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Volumetric coarse fragments content (v%) of the soil whole earth, aggregated over rootable depth and the top 30 cm, mapped at 1km resolution
    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

  • A Globally Distributed Soil Spectral Library Mid Infrared Diffuse Reflectance... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The ICRAF-ISRIC Soil MIR Spectral Library contains visible near infrared spectra of 4,438 soils selected from the Soil Information System (ISIS) of the International Soil Reference and Information Centre (ISRIC). The samples consist of all physically archived samples at ISRIC in 2004 for which soil attribute data was available. The spectra were measured...
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - Coarse fragments volumetric aggregated 5000m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Coarse fragments volumetric in cm3/dm3 (vol‰) 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 5000 m cell.
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2.0 - Soil organic carbon content aggregated 5000m N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil organic carbon content (fine earth fraction) in dg/kg 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. 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

  • SoilGrids250m 2017-03 - Soil organic carbon stock in tons per ha at 3 IPCC de... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Soil organic carbon stock in tons per ha for ICCP depth intervals 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: t / ha.
    Created October 25, 2023 • Updated October 25, 2023

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

    FDRE - Ministry of Agriculture (MoA)
    Sand content (50/63-2000 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

  • SoilGrids250m 2017-03 - Derived available soil water capacity (volumetric fra... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Derived available soil water capacity (volumetric fraction) with FC = pF 2.5 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...
    Created October 25, 2023 • Updated October 25, 2023

  • Africa SoilGrids - Root zone total plant available water holding capacity agg... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Total plant-available water holding capacity (mm) of the soil whole earth fraction (including coarse fragments), summed over rootable depth and the top 30 cm, mapped at 1km resolution
    Created October 25, 2023 • Updated October 25, 2023

  • IPCC default soil classes derived from the Harmonized World Soil Data Base, v... N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    This global data set shows the spatial distribution of generalized soil classes as defined for IPCC Tier-I level national greenhouse gas inventory assessments. The database was derived from the Harmonized World Soil Data Base (HWSD ver. 1.1, at scale 1:1-1:5 M) and a series of taxotransfer procedures to convert FAO soil classifications (1974, 1985 and...
    Created October 25, 2023 • Updated October 25, 2023

  • 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

  • SoilGrids250m 2017-03 - Texture class (USDA system) N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Texture class (USDA system) 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')
    Created October 25, 2023 • Updated October 25, 2023

  • SOTER-based soil parameter estimates (SOTWIS) for Central Africa N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    This harmonized set of soil parameter estimates for Central Africa, comprising Burundi, the Democratic Republic of the Congo and Rwanda, was derived from the Soil and Terrain Database for Central Africa (SOTERCAF ver. 1.0) and the ISRIC-WISE soil profile database, using standardized taxonomy-based pedotransfer (taxotransfer) procedures. The land surface...
    Created October 25, 2023 • Updated October 25, 2023

  • Soil and Terrain Database (SOTER) for Nepal N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Soil and Terrain database for Nepal primary data (version 1.0), at scale 1:1 million (SOTER_Nepal). SOTER_Nepal is generalized from the original Soils and Terrain database of Nepal at scale 1:50,000 compiled by FAO and Nepal's Survey Dept. The SOTER_Nepal database provides generalized information on landform and soil properties at a scale 1:1 million....
    Created October 25, 2023 • Updated October 25, 2023

  • SoilGrids250m 2017-03 - Predicted probability WRB 2006 subgroup 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. Legend: 1: "Haplic Acrisols", 2:...
    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

  • SoilGrids250m 2017-03 - Coarse fragments volumetric N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    Coarse fragments volumetric 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: v%.
    Created October 25, 2023 • Updated October 25, 2023

  • Soil and Terrain Database (SOTER) for China N3 | TTL | RDF/XML | JSON-LD

    FDRE - Ministry of Agriculture (MoA)
    The Soil and Terrain database for China primary data (version 1.0), at scale 1:1 million (SOTER_China), was compiled of enhanced soil information within the framework of the FAO's program of Land Degradation Assessment in Drylands (LADA). The primary database was compiled using the SOTER methodology. The SOTER unit delineation was based on a raster format...
    Created October 25, 2023 • Updated October 25, 2023

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

    FDRE - Ministry of Agriculture (MoA)
    Predicted USDA 2014 suborder 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
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