The organic carbon content (in mass-%) map for the 0-10-cm soil layer of the United Republic of Tanzania was generated by means of digital soil mapping in a regression-kriging framework (‘Simple kriging with varying local means’) implemented in the Open Source Software R. Over 3,000 soil point observations were used to generate the map. Data sources were NAFORMA, Tanzania National Soil Survey, African Soil Profiles Database Version 1.1, and AfSIS. In addition a suite of environmental GIS data layers were used such as a land cover map, SOTER soil class map, maps of topographic attributes derived from the SRTM-DEM, maps of surface reflectance and vegetation indices derived from satellite imagery. The point observations were correlated to the environmental data layers using a linear regression model. This model was used to predict the carbon content at the nodes of a regular grid with 250 meter cell size. The regression residuals were kriged to the prediction grid nodes and added to the regression prediction to obtain the final prediction of carbon content. Map projection is UTM Zone 36S.The root mean square error, as determined through 10-fold cross-validation, is 0.89%. The map was produced by ISRIC - World Soil Information in a collaborative effort with the National Soil Survey, Ministry of Natural Resources and Tourism, Tanzania Forest Services, Sokoine University, and AfSIS.
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 standardised in accordance with the licences specified by the data providers. Soil profile data managed in WoSIS were contributed by a wide range of data providers, therefore special attention was paid to measures for soil data quality and the standardisation of soil property definitions, soil property values (and units of measurement), and soil analytical method descriptions. We presently consider the following soil chemical properties (organic carbon, total carbon, total carbonate equivalent, total Nitrogen, Phosphorus (extractable-P, total-P, and P-retention), soil pH, cation exchange capacity, and electrical conductivity) and physical properties (soil texture (sand, silt, and clay), bulk density, coarse fragments, and water retention), grouped according to analytical procedures (aggregates) that are operationally comparable. Further, for each profile, we provide the original soil classification (FAO, WRB, USDA, and version) and horizon designations insofar as these have been specified in the source databases. Measures for geographical accuracy (i.e. location) of the point data as well as a first approximation for the uncertainty associated with the operationally defined analytical methods are presented, for possible consideration in digital soil mapping and subsequent earth system modelling. The present snapshot, referred to as ‘WoSIS snapshot - September 2019’, comprises 196,498 geo-referenced profiles originating from 173 countries. They represent over 832 thousand soil layers (or horizons), and over 6 million records. The actual number of observations for each property varies (greatly) between proﬁles and with depth, this generally depending on the objectives of the initial soil sampling programmes. Citation: Batjes N.H, Ribeiro E, and van Oostrum A.J.M, 2019. Standardised soil profile data for the world (WoSIS snapshot - September 2019), https://doi.org/10.17027/isric-wdcsoils.20190901. The dataset accompanies the following data paper (submitted): Batjes N.H., Ribeiro E., and van Oostrum A.J.M., 2019. Standardised soil profile data to support global mapping and modelling (WoSIS snapshot - 2019). Earth System Science Data Discussions, https://doi.org/10.5194/essd-2019-164