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201 datasets found
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WoSIS latest - Organic matter N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Gravimetric content of organic matter in the fine earth fraction (g/kg). (LOI). WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil data served from WoSIS (ISRIC World Soil Information Service). The source data were shared by a wide range of data providers (see:...Created April 17, 2024 • Updated April 17, 2024 -
WoSIS latest - Sites N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)This file provides an overview of the site locations where profiles (or point data) in WoSIS are located. Depending on the type of survey, one or more profiles can occur within a site in accordance with ISO 28528 soil domain conventions. WoSIS_latest is a 'dynamic dataset' that contains the most recent complement of quality-assessed and standardised soil...Created April 17, 2024 • Updated April 17, 2024 -
SoilGrids250m 2.0 - Volumetric Water Content at 33kPa aggregated 5000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 33kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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 (Turek et...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 -
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 -
SoilGrids250m 2.0 - Volumetric Water Content at 1500kPa N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 1500kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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.Created October 25, 2023 • Updated November 25, 2023 -
SoilGrids250m 2.0 - Volumetric Water Content at 1500kPa aggregated 1000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 1500kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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 (Turek...Created October 25, 2023 • Updated November 25, 2023 -
SoilGrids250m 2.0 - Volumetric Water Content at 1500kPa aggregated 5000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 1500kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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 (Turek...Created October 25, 2023 • Updated November 25, 2023 -
SoilGrids250m 2.0 - Volumetric Water Content at 10kPa aggregated 1000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 10 kPa suction in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) 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 (Turek...Created October 25, 2023 • Updated November 25, 2023 -
SoilGrids250m 2.0 - Silt content aggregated 1000m 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each...Created October 25, 2023 • Updated October 25, 2023 -
Global Assessment of Human-induced Soil Degradation (GLASOD) N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)The GLASOD project (1987-1990), carried out for UNEP, has produced a world map of human-induced soil degradation. Data were compiled in cooperation with a large number of soil scientists throughout the world, using uniform Guidelines and international correlation. The status of soil degradation was mapped within loosely defined physiographic units...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 - Sand content (50-2000 micro meter) mass fraction N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Sand content (50-2000 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 - Total nitrogen aggregated 5000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Total nitrogen in cg/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 each 5000 m cell.Created October 25, 2023 • Updated October 25, 2023 -
SoilGrids250m 2017-03 - Bulk density (fine earth) N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)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.Created October 25, 2023 • Updated October 25, 2023 -
SoilGrids250m 2.0 - Sand content aggregated 5000m 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each...Created October 25, 2023 • Updated October 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 2.0 - Sand content aggregated 1000m 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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each...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 -
SoilGrids250m 2.0 - Bulk density aggregated 1000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Bulk density (fine earth) in cg/cm³ 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 1000 m cell.Created October 25, 2023 • Updated October 25, 2023
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