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SoilGrids data layers

Source: R/get_soilgrids.R
soilgrids.Rd

SoilGrids is a project combining global observation data with machine learning to map the spatial distribution of soil properties across the globe. It is produced at a spatial resolution of 250 meters and each parameter is mapped at different depths. In order to be able to assess prediction uncertainty, besides the mean and median prediction, the 0.05 and 0.95 percentile predictions are available. The following parameters are available:

bdod

Bulk density of the fine earth fraction (kg/dm3)

cec

Cation Exchange Capacity of the soil (cmol(c)/kg)

cfvo

Volumetric fraction of coarse fragments > 2 mm (cm3/100cm3 (volPerc))

clay

Proportion of clay particles < 0.002 mm in the fine earth fraction (g/100g)

nitrogen

Total nitrogen (g/kg)

phh2o

Soil pH (pH)

sand

Proportion of sand particles > 0.05 mm in the fine earth fraction (g/100g)

silt

Proportion of silt particles >= 0.002 mm and <= 0.05 mm in the fine earth fraction (g/100g)

soc

Soil organic carbon content in the fine earth fraction (g/kg)

ocd

Organic carbon density (kg/m3)

ocs

Organic carbon stocks (kg/m²)

Usage

get_soilgrids(layers, depths, stats)

Source

https://www.isric.org/explore/soilgrids

Arguments

layers

A character vector indicating the layers to download from soilgrids

depths

A character vector indicating the depths to download

stats

A character vector indicating the statistics to download.

Value

A function that returns an sf footprint object.

Details

Except for ocs, which is only available for a depth of "0-30cm", all other parameters are available at the following depths:

  • "0-5cm"

  • "5-15cm"

  • "15-30cm"

  • "30-60cm"

  • "60-100cm"

  • "100-200cm"

Each parameter and depth is available for the following statistics:

  • "Q0.05"

  • "Q0.50"

  • "mean"

  • "Q0.95"

References

Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., and Rossiter, D.: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7, 217–240, 2021. doi:10.5194/soil-7-217-2021