SoilGrids1km — Global Soil Information Based on Automated Mapping

Abstract

BackgroundSoils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail.Methodology/Principal FindingsWe present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%.Conclusions/SignificanceSoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license.

The pyrogeography of eastern boreal Canada from 1901 to 2012 simulated with the LPJ-LMfire model

“…In the present study, simulations are limited by the relatively low accuracy of soil attributes in databases for Canada's boreal forest (Hengl et al, 2014). The input data set of soil attributes that was used in our simulations tended to underestimate clay and sand percentages in our study area when compared to point observations (Fig.…”

“…The volume fraction of coarse fragments together with the 0-100 cm deep soil texture fractions of sand and clay were interpolated on the 10 × 10 km grids from the 1 km resolution ISRIC -World Soil Information data set (Hengl et al, 2014). For topography, we interpolated the 30 arcsec gridded digital elevation model (DEM) of Canada (Natural Resources Canada, 2007).…”

“…Edaphic limits to establishment were defined here in the same way that bioclimatic limits are used in LPJ. The correlations between the genus-specific tree cover fraction from Beaudoin et al (2014) and clay volume fraction from Hengl et al (2014) were analyzed at a 10 km resolution. For each PFT, the percentage of clay corresponding to the upper limit of the 90 % confidence interval (CI) of its distribution, for grid cells with at least 10 % of PFT cover, was used in the model as a threshold above which the given PFT could not establish.…”

Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin

“…Three thousand hectares (76%) of agricultural land is irrigated. The soil map used in this study originates from the International Soil Reference Information Centre (ISRIC) [61] and Food and Agricultural Organization (FAO) Digital Soil Map of the World [62]. The SoilGrids database (ISRIC, Wageningen, The Netherlands) has a spatial resolution of 1 km × 1 km, and is produced during 2014.…”

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

“…However, there are challenges that limit SSURGO's use for other purposes including: variable quality and spatial detail between soil surveys, artificial discontinuities at political boundaries, and incomplete spatial coverage (Zhu et al, 2001;Gatzke et al, 2011;Thompson et al, 2012;Subburayalu and Slater, 2013;Du et al, 2014;. These challenges must be addressed to fully use SSURGO in contemporary applications such as climate and hydrologic models that require high quality and spatially complete soil information over continental extents (Wood et al, 2011;Bierkens et al, 2014;Chaney et al, 2014;Hengl et al, 2014). One promising path forward is through digital soil mapping (DSM).…”