ISRIC Data Hub
ISRIC Data Hub (ISRIC - World Soil Information)
Continents, countries, sea regions of the world.
WoSIS latest - Bulk density whole soil - air dry
Bulk density of the whole soil including coarse fragments, 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.
Licenced per profile, as specified by data provider and indicated in the data
Total nitrogen (N) content in g/kg of the fine earth fraction in 2 depth intervals (0-20 cm and 20-50 cm) measured according to the analytical procedures of wet oxidation and 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)
Attribution-NonCommercial 3.0 International (CC BY-NC 3.0), https://creativecommons.org/licenses/by-nc/3.0/
Project webpages: http://africasoils.net/ http://isric.org/projects/africa-soil-information-service-afsis Soil data (1): http://isric.org/projects/africa-soil-profiles-database-afsp Not included: Soil data (2): http://africasoils.net/services/data/soil-databases/
SoilGrids250m 2.0 - Soil organic carbon content aggregated 5000m
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 each 5000 m cell.
Attribution 4.0 International (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/
https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts https://doi.org/10.5194/soil-7-217-2021
SoilGrids250m 2.0 - Silt content aggregated 1000m
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 1000 m cell.
Africa SoilGrids nutrients - Extractable Aluminium (Al)
Extractable Aluminium (Al) 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.
Project webpage: http://isric.org/projects/africa-soilgrids-soil-nutrient-maps-sub-saharan-africa-250-m-resolution Soil data (1): http://isric.org/projects/africa-soil-profiles-database-afsp Soil data (2): http://africasoils.net/services/data/soil-databases/
GeoPearl: SOM-content under arable land 1000m
Model predictions on SOM-content under arable land( Report: https://edepot.wur.nl/556312). Predictions with a model ensemble at fixed depths of 15, 45, 80 and 120 cm. Predictions using an ensemble of Random Forests and Gradient Boosting, with covariates from the SoilGrids 2017 model (Hengl et al. 2017) and a spatial cross-validation procedure. The model was applied on log-transformed observations of SOC. Models result were back- transformed and converted to SOM by multiplying SOC predictions with 1.743. Prediction
Soil information, from the global to the local scale, has often been the one missing biophysical information layer, the absence of which has added to the uncertainties of predicting potentials and constraints for food and fiber production. The lack of reliable and harmonized soil data has considerably hampered land degradation assessments, environmental impact studies and adapted sustainable land management interventions. Recognizing the urgent need for improved soil information worldwide, particularly in the context of the Climate Change Convention and the Kyoto Protocol for soil carbon measurements and the immediate requirement for the FAO/IIASA Global Agro-ecological Assessment study (GAEZ v3.0), the Food and Agriculture Organization of the United Nations (FAO) and the International Institute for Applied Systems Analysis (IIASA) took the initiativeof combining the recently collected vast volumes of regional and national updates of soil information with the information already contained within the 1:5,000,000 scale FAOUNESCO Digital Soil Map of the World, into a new comprehensive Harmonized World Soil Database (HWSD). This database was achieved in partnership with: • ISRIC-World Soil Information together with FAO, which were responsible for the development of regional soil and terrain databases and the WISE soil profile database; • the European Soil Bureau Network, which had recently completed a major update of soil information for Europe and northern Eurasia, and • the Institute of Soil Science, Chinese Academy of Sciences which provided the recent 1:1,000,000 scale Soil Map of China.
Repositório Brasileiro Livre para Dados Abertos do Solo
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 dataset-driven structure helps datasets authors to be properly acknowledged. Moreover, it gives the flexibility to accommodate many types of data of any soil variable. This is accomplished by storing each dataset using a collection of spreadsheets accessible through an online application. Spreadsheets are familiar to any soil scientist, the reason why it is easier to enter, manipulate and visualize soil data in febr. They also facilitate the participation of soil survey experts in the recovery and quality assessment of legacy data. Soil scientists can help in the definition of standards and data management choices through a public discussion forum, febr-forum@googlegroups.com. A comprehensive documentation is available to guide febr maintainers and data contributors. A detailed catalog gives access to the 14 477 soil observations – 42% of them from south and southeastern Brazil – from 232 datasets contained in febr. Global and dataset-specific visualization and search tools and multiple download facilities are available. The latter includes standard file formats and connections with R and QGIS through the febr package. Various products can be derived from data in febr: specialized databases, pedotransfer functions, fertilizer recommendation guides, classification systems, and detailed soil maps. By sharing data through a centralized soil data storing and sharing facility, soil scientists from different fields have the opportunity to increase collaboration and the much needed soil knowledge.
Soil and Terrain Database (SOTER) for South Africa
The Soil and Terrain database for South Africa primary data (version 1.0), at scale 1:1 million (SOTER_South_Africa), 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 South Africa were obtained from the SOTERSAF database (ver. 1) at scale 1:2 million. This version of SOTER_South_Africa includes some changes in the GIS file, based on the SRTM-DEM derived data and a 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.
Attribution 3.0 International (CC BY 3.0)
Primary data: 1) Dijkshoorn JA 2003. SOTER database for southern Africa (SOTERSAF, ver. 1.0), ISRIC - World Soil Information, Wageningen 2) FAO and ISRIC 2003. Soil and Terrain database for Southern Africa (1:2 million scale). FAO Land and Water Digital Media Series 25, ISRIC and FAO, Rome (http://www.fao.org/icatalog/search/dett.asp?aries_id=104318) Derived data (needed for modelling): 3) Batjes NH 2004. SOTER-based soil parameter estimates for Southern Africa (ver. 1.0). Report 2004/04, ISRIC - World Soil Information, Wageningen, https://isric.org/sites/default/files/isric_report_2004_04.pdf
WoSIS latest - Calcium carbonate equivalent total
The content of carbonate in a liming material or calcareous soil calculated as if all of the carbonate is in the form of CaCO3 (in the fine earth fraction*); also known as inorganic carbon (g/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.
Joint Research Centre of the European Commission - European Soil Data Centre (ESDAC)
International Institute for Applied Systems Analysis
Food and Agriculture Organization of the United Nations
Institute of Soil Science - Chinese Academy of Sciences
Universidade Tecnológica Federal do Paraná - Câmpus Santa Helena
ISRIC - World Soil Information (WDC - Soils)
A measure of the acidity or alkalinity in soils, defined as the negative logarithm (base 10) of the activity of hydronium ions (H+) in a CaCl2 solution, as specified in the analytical method descriptions. 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.
SoilGrids250m 2.0 - Volumetric Water Content at 33kPa aggregated 5000m
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 al. 2021) for each 5000 m cell.
https://www.isric.org/explore/wosis/wosis-contributing-institutions-and-experts https://doi.org/10.1016/j.iswcr.2022.08.001
SoilGrids250m 2017-03 - Silt content (2-50 micro meter) mass fraction
Silt content (2-50 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%.
SoilGrids250m 2.0 - Soil organic carbon stock
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.
Scientific publication (Turek et al. 2021)