Datasets

FDRE - Ministry of Agriculture (MoA)

Africa SoilGrids - Exchangeable sodium (Na+)

Exchangeable sodium (Na+ measured in 1M NH4OAc buffered at pH 7 with part of the data converted from data measured according to Mehlich 3) in cmolc/kg (fine earth) at 2 depth intervals (0-20 cm and 20-50 cm) predicted using two Africa soil profiles datasets. 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, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

• Africa
• Soil science
• digital soil mapping
• nutrients
• +1 more

FDRE - Ministry of Agriculture (MoA)

Africa SoilGrids - Silt content

Silt content (2-50 micro meter) in g/100g (w%) at 6 standard depths 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, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

• Africa
• Soil science

FDRE - Ministry of Agriculture (MoA)

SoilGrids250m 2.0 - Bulk density aggregated 5000m

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 5000 m cell.

• Global
• Soil science

FDRE - Ministry of Agriculture (MoA)

Soil and Terrain Database (SOTER) for Malawi

The Soil and Terrain database for Malawi (version 1.0), at scale 1:1 million, was compiled based on the soil map of Malawi at scale 1:250,000 (compiled by the Land Resources Evaluation Project) that was complemented with soil boundary information from the provisional soil map at scale 1:1 million. The 90m SRTM-DEM was used to define the various landform types of the SOTER units and also to adjust their boundaries. The SOTER map units were attributed with soil information obtained from the Africa Soil Profiles Database. The SOTER compilation followed the methodology described in the SOTER Procedures Manual Version 2. SOTER forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts. DOI for dataset (submitted): 10.17027/isric.wdcsoils.20160002

FDRE - Ministry of Agriculture (MoA)

SoilGrids250m 2017-03 - Derived saturated water content (volumetric fraction) teta-S

Derived saturated water content (volumetric fraction) teta-S 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%.

• Global
• Soil science

FDRE - Ministry of Agriculture (MoA)

Africa SoilGrids nutrients - Extractable Magnesium (Mg)

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 Africa Soil Profiles database (AfSP) compiled by AfSIS and recent soil data newly collected by AfSIS in partnership with EthioSIS (Ethiopia), GhaSIS (Ghana) and NiSIS (Nigeria as made possible by OCP Africa and IITA), combined with soil data as made available by Wageningen University and Research, IFDC, VitalSigns, University of California and the OneAcreFund. [Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutriënt Cycling in Agroecosystems 109(1): 77-102). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.

FDRE - Ministry of Agriculture (MoA)

Africa SoilGrids nutrients - Extractable Phosphorus (P)

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 from the Africa Soil Profiles database (AfSP) compiled by AfSIS and recent soil data newly collected by AfSIS in partnership with EthioSIS (Ethiopia), GhaSIS (Ghana) and NiSIS (Nigeria as made possible by OCP Africa and IITA), combined with soil data as made available by Wageningen University and Research, IFDC, VitalSigns, University of California and the OneAcreFund. [Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutriënt Cycling in Agroecosystems 109(1): 77-102). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.

FDRE - Ministry of Agriculture (MoA)

Soil and Terrain Database (SOTER) for Nepal

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. It consists of 17 SOTER units, ... characterized by 56 representative and four synthetic profiles for which there are no measured soil data. The SOTER database includes also attribute data of 99 profiles initially selected as references to soil components that have already a representative profile. SOTER forms a part of the ongoing activities of ISRIC and FAO to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts

FDRE - Ministry of Agriculture (MoA)

Soil and Terrain Database (SOTER) for Argentina

The Soil and Terrain database for Argentina primary data (version 1.0), at scale 1:1 million (SOTER_Argentina), was compiled of enhanced soil information within the framework of the FAO's program Land Degradation Assessment in Drylands (LADA). Primary soil and terrain data for Argentina were obtained from the SOTERLAC database (ver. 2) at scale 1:5 million. This update includes considerable changes in the GIS file, based on the SRTM-DEM derived surface information and on INTA's digital soil map (Instituto de Suelos), and only few changes of the attributes database. SOTER forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts.

FDRE - Ministry of Agriculture (MoA)

Africa SoilGrids nutrients - Extractable Potassium (K)

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 predicted. using soil data from the Africa Soil Profiles database (AfSP) compiled by AfSIS and recent soil data newly collected by AfSIS in partnership with EthioSIS (Ethiopia), GhaSIS (Ghana) and NiSIS (Nigeria as made possible by OCP Africa and IITA), combined with soil data as made available by Wageningen University and Research, IFDC, VitalSigns, University of California and the OneAcreFund. [Values M = mean value predicted]. For details see below for peer reviewed paper (T. Hengl, J.G.B. Leenaars, K.D. Shepherd, M.G. Walsh, G.B.M. Heuvelink, Tekalign Mamo, H. Tilahun, E. Berkhout, M. Cooper, E. Fegraus, I. Wheeler, N.A. Kwabena, 2017. Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutriënt Cycling in Agroecosystems 109(1): 77-102). Maps produced for the Environmental Assessment Agency (PBL), funded by the Netherlands government, in collaboration with the AfSIS and the Vital Signs projects.