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    This data was collected to develop baselines for three Land Degradation Neutrality (LDN) indicators: land use and land cover change (LUC) for the period 2001-2017, soil organic carbon (SOC) stocks for 2017 and bush density for 2017 as a baseline for bush encroachment in Omusati region, Namibia.

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    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. The downloadable ZIP file has the data in TSV (tab separated values) and GeoPackage format. It contains the following files: - ReadmeFirst_WoSIS_2019dec04.pdf (546.7 KB) - wosis_201909.gpkg (2.2 GB, same data as in the tsv) - wosis_201909_attributes.tsv (8.7 KB) - wosis_201909_layers_chemical.tsv (893.5 MB) - wosis_201909_layers_physical.tsv (890.7 MB) - wosis_201909_profiles.tsv (18.8 MB) To read the data in R, please, uncompress the ZIP file and specify the uncompressed folder. Then use read_tsv to read the TSV files, specifying the data types for each column (c = character, i = integer, n = number, d = double, l = logical, f = factor, D = date, T = date time, t = time). setwd("/YourFolder/WoSIS_2019_September/") attributes = readr::read_tsv('wosis_201909_attributes.tsv', col_types='cccciicd') profiles = readr::read_tsv('wosis_201909_profiles.tsv', col_types='icccdddiicccciccccicccc') chemical = readr::read_tsv('wosis_201909_layers_chemical.tsv', col_types='iiddclcdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccc') physical = readr::read_tsv('wosis_201909_layers_physical.tsv', col_types='iiddclcdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccccdccccc') For more detailed instructions on how to read the data with R, please visit https://www.isric.org/accessing-wosis-using-r. 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: 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, https://doi.org/10.5194/essd-12-299-2020.

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    This soil organic carbon dataset contains the following maps: soil organic carbon concentration (%) for the 0-10 cm, 10-20 cm, 20-30 cm and 0-30 cm soil layers, and bulk density (kg/m3) and soil organic carbon stock (kg/m2) for the 0-30 cm layer. These maps were produced with (geostatistical) regression-kriging models that combined soil data from the NAFORMA survey, the Tanzania National Soil Survey and the African Soil Profiles Database Version 1.1 with a suite of environmental GIS data layers including 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 regression-kriging models were used to predict carbon concentrations, stocks and bulk density at the nodes of a regular grid with 250 meter cell size covering the Tanzania. Prediction uncertainty was quantified and is available with the data as the lower and upper boundary of the 90% prediction interval. Further details about the input data, modelling framework, and cross validation results are provided in a peer-reviewed, scientific journal article. The project was funded by the UN-REDD Programme Output 2.4 “National Maps inform delivery of the REDD+ Framework” and conducted through a letter of Agreement between Food and Agricultural Organization of the United Nations (FAO) and ISRIC-World Soil Information. The maps were 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 the AfSIS project.