Organic Carbon Content in Soil
SoilGrids1km contains spatial predictions for a selection of soil properties (at six standard depths) including sand, silt and clay fractions as well as soil organic carbon stocks. Predictions are based on global spatial prediction models which were fitted, per soil variable, using a compilation of major international soil profile databases (~110,000 soil profiles), and a selection of ~75 global environmental covariates representing soil forming factors. HydroATLAS provides data for the 0-5 cm top soil layer.
Reference
Hengl, T., de Jesus, J.M., MacMillan, R.A., Batjes, N.H., Heuvelink, G.B., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J., Walsh, M., Gonzalez, M.R. (2014). SoilGrids1km—global soil information based on automated mapping. PLoS ONE, 9(8), e105992.
License
Open Data Commons Open Database License (ODbL v1.0)
Additional Information
Original grid contains NoData pixels (mostly in deserts and within open water surfaces such as lakes) which were excluded from average calculations. Value -9999 indicates that there is no data for the entire spatial unit.
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Borrelli, P., Robinson, D.A., Fleischer, L.R., Lugato, E., Ballabio, C., Alewell, C., Meusburger, K., Modugno, S., Schütt, B., Ferro, V., Bagarello, V., Van Oost, K., Montanarella, L., Panagos, P. (2017). An assessment of the global impact of 21st century land use change on soil erosion. Nature Communication, 8, 2013.
GloSEM erosion estimates were produced with a high resolution (250 × 250 m) global potential soil erosion model, using a combination of remote sensing, GIS modelling and census data. The long-term annual soil erosion rates were estimated using an improved large-scale version of the Revised Universal Soil Loss Equation (RUSLE) model. RUSLE belongs to the so-called detachment-limited model types where the soil erosion (expressed as a mass of soil lost per unit area and time) due to inter-rill and rill erosion processes is given by the multiplication of six contributing factors. Consistent with the predictive capacity of the model, soil displacement due to processes such as gullying and tillage erosion is not estimated.
Döll, P., Kaspar, F., Lehner, B. (2003). A global hydrological model for deriving water availability indicators: model tuning and validation. Journal of Hydrology, 270, 105-134.
Discharge and runoff estimates for HydroATLAS are based on long-term (1971–2000) average ‘naturalized’ discharge and runoff values provided by the state-of-the-art global integrated water balance model WaterGAP (Döll et al. 2003, model version 2.2 as of 2014). The WaterGAP data were spatially downscaled from their original 0.5 degree pixel resolution (~50 km at the equator) to the 15 arc-second (~500 m) resolution of the HydroSHEDS river network using geo-statistical techniques (Lehner and Grill 2013). Preliminary tests against approximately 3000 global gauging stations indicate a good overall correlation for the long-term averages, but also reveal larger uncertainties, in particular in the minimum and maximum statistics, for areas that are dominated by snow, glaciers, wetlands, and (semi-)arid conditions.
Zomer, R.J., Trabucco, A., Bossio, D.A., van Straaten, O., Verchot, L.V. (2008). Climate change mitigation: A spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agriculture, Ecosystems & Environment, 126(1), 67-80.
The Global Aridity Index (Global-Aridity) is modeled using data from WorldClim as input parameters. Aridity is usually expressed as a generalized function of precipitation, temperature, and/or potential evapotranspiration (PET). For this global aridity index, it was calculated as mean annual precipitation over mean annual PET, i.e. rainfall over vegetation water demand (aggregated on an annual basis). Under this formulation, the aridity index values increase with more humid conditions, and decrease with more arid conditions. An aridity index value of 0 represents areas of no preciptiation, a value of 1 represent areas where precipitation equals PET, and a value >1 represents areas where precipitation exceeds PET. Note that maximum values were capped at 100.
UNEP-WCMC and IUCN (UN Environment World Conservation Monitoring Centre and International Union for Conservation of Nature) (2014). The World Database on Protected Areas (WDPA). UNEP-WCMC and IUCN, Cambridge, UK. Available at: www.protectedplanet.net.
The World Database on Protected Areas (WDPA) is the most comprehensive global database of marine and terrestrial protected areas. It is a joint effort between IUCN and UNEP, managed by UNEP-WCMC, to compile protected area information for all countries in the world from governments and other authoritative organizations. HydroATLAS includes all nationally designated PAs (DESIG TYPE = “national”; STATUS = “designated”) of all IUCN categories (IUCN CAT = “I-VI,” “not reported,” or “not assigned”) from the October 2014 version of WDPA (160,000 polygons representing 19.2 million km2). In cases where PA sites were only given as point data (17,000 points representing 1.1 million km2), their spatial extent was approximated as a circle with a size representing the reported area.