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.
Absolute depth to bedrock (in cm) 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: cm.
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 derived from the ISRIC-WISE soil database. The land surface between longitudes -180o W and +180o E and latitudes +90o N and -90o S has been characterized using 45948 unique map units; each of these can comprise from one to ten soil units, characterized according to the original legend of the 1:5 million scale Soil Map of the World (FAO-Unesco 1974). Soil parameter estimates for each of these units were derived from analyses of some 9600 profiles held in a working copy of WISE (ver. 2.0). Twenty-two soil variables, identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil gaseous emissions and analyses of global environmental change, were considered. Parameter estimates for the topsoil (0-30 cm) and the subsoil (30-100 cm) are presented for the following variables: content of organic carbon, total nitrogen, the C/N ratio, pH(H2O), CECsoil, CECclay, base saturation, total exchangeable bases, aluminum saturation, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), calcium carbonate content, gypsum content, content of sand, silt and clay, content of fragments less than 2 mm, bulk density, total porosity. For soil drainage class, effective soil depth, and available water capacity (-10 to -1500 kPa), however, parameter estimates are presented on a profile basis. The parameter estimates - median values - presented here should be seen as best estimates; possible types and sources of uncertainty are discussed in the report. The data are considered appropriate for exploratory studies at global scale (greater than 1:5 000 000). Note: A more recent assessment, at a resolution of 30arcsec (WISE30sec), is available at: http://data.isric.org/geonetwork/srv/eng/catalog.search#/metadata/dc7b283a-8f19-45e1-aaed-e9bd515119bc
Soil organic carbon density in hg/m³ 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.
Bulk density of the fine earth fraction*, air dried (kg/dm³). 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: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
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 al. 2021) for each 5000 m cell.
Measured in 1:x soil:water solution (mainly determines P in dissolved forms) (mg/kg). 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: https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts). Being dynamic, the contents of 'wosis_latest' will change once new point data are acquired, cleansed and standardised, additional soil properties are considered, and/or when possible amendments are required. Static snapshots of 'wosis_latest' are released at irregular intervals for consistent citation purposes and to discuss methodological changes; the last snapshot is available at https://doi.org/10.5194/essd-16-4735-2024. For general information about WoSIS please see the FAQ-page at https://www.isric.org/explore/wosis/faq-wosis.
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. To visualize these layers please use www.soilgrids.org.
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 1000 m cell.
Soil organic carbon stock in t/ha for 0-30 cm depth interval. 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.