Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale. The short description of currently available soil properties: soil pH in H2O; Soil properties were predicted at fixed depths: Surface soil = s0..0cm, Subsoil 1 = s30..30cm, Subsoil 2 = s60..60cm, Subsoil 3 = s100..100cm. To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula. Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020
Uncertainties associated with legacy data contribute to the spatial uncertainty of predictions for s...
The Swiss Soil Property Map (SSPM) was developed using the quantile random forest machine learning a...
Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Accurate and high resolution spatial soil information is essential for efficient and sustainable lan...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
This paper describes the technical development and accuracy assessment of the most recent and improv...
SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m ...
Soil pH in H2O in × 10 at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Pro...
iSDAsoil dataset soil pH (1:1 Soil-Water Suspension) predicted at 30 m resolution for 0–20 and 20–50...
Volumetric Water Content at 10kPa in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictio...
Volumetric Water Content at 10kPa in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictio...
Uncertainties associated with legacy data contribute to the spatial uncertainty of predictions for s...
The Swiss Soil Property Map (SSPM) was developed using the quantile random forest machine learning a...
Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environ...
Accurate and high resolution spatial soil information is essential for efficient and sustainable lan...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
This paper describes the technical development and accuracy assessment of the most recent and improv...
SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m ...
Soil pH in H2O in × 10 at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Pro...
iSDAsoil dataset soil pH (1:1 Soil-Water Suspension) predicted at 30 m resolution for 0–20 and 20–50...
Volumetric Water Content at 10kPa in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictio...
Volumetric Water Content at 10kPa in 10-3 cm3cm-3 (0.1 v% or 1 mm/m) at 6 standard depths. Predictio...
Uncertainties associated with legacy data contribute to the spatial uncertainty of predictions for s...
The Swiss Soil Property Map (SSPM) was developed using the quantile random forest machine learning a...
Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As ...