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8 datasets found
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SoilGrids250m 2.0 - Volumetric Water Content at 10kPa aggregated 5000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 10kPa 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 October 25, 2023 • 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 -
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 -
Repositório Brasileiro Livre para Dados Abertos do Solo N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)The Free Brazilian Repository for Open Soil Data – febr, www.ufsm.br/febr – is a centralized repository targeted at storing open soil data and serving it in a standardized and harmonized format. The repository infrastructure was built using open source and/or free (of cost) software, and was primarily designed for the individual management of datasets. A...Created October 25, 2023 • Updated October 25, 2023 -
SoilGrids250m 2.0 - Volumetric Water Content at 33kPa aggregated 1000m N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Volumetric Water Content at 33kPa 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 al....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 -
Global mangrove soil carbon: dataset and spatial maps N3 | TTL | RDF/XML | JSON-LD
FDRE - Ministry of Agriculture (MoA)Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions...Created October 25, 2023 • Updated October 25, 2023
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