iSDAsoil Organic Carbon

ISDASOIL/Africa/v1/carbon_organic
Dataset Availability
2001-01-01T00:00:00Z - 2017-01-01T00:00:00
Dataset Provider
Earth Engine Snippet
ee.Image("ISDASOIL/Africa/v1/carbon_organic")
Tags
africa carbon carbon-organic isda soil

Description

Organic carbon at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation.

Pixel values must be back-transformed with exp(x/10)-1.

In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artefacts such as banding (striping) might be seen. Soil property predictions were made by Innovative Solutions for Decision Agriculture Ltd. (iSDA) at 30 m pixel size using machine learning coupled with remote sensing data and a training set of over 100,000 analyzed soil samples. Further information can be found in the FAQ and technical information documentation. To submit an issue or request support, please visit the iSDAsoil site.

Bands

Resolution
30 meters

Bands

Name Units Min Max Description
mean_0_20 g/kg 1 46

Carbon, organic, predicted mean at 0-20 cm depth

mean_20_50 g/kg 0 46

Carbon, organic, predicted mean at 20-50 cm depth

stdev_0_20 g/kg 0 12

Carbon, organic, standard deviation at 0-20 cm depth

stdev_20_50 g/kg 0 13

Carbon, organic, standard deviation at 20-50 cm depth

Terms of Use

Terms of Use

CC-BY-4.0

Citations

Citations:
  • Hengl, T., Miller, M.A.E., Križan, J., et al. African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. Sci Rep 11, 6130 (2021). doi:10.1038/s41598-021-85639-y

Explore in Earth Engine

var mean_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#000004" label="0-2.3" opacity="1" quantity="12"/>' +
  '<ColorMapEntry color="#0C0927" label="2.3-3.5" opacity="1" quantity="15"/>' +
  '<ColorMapEntry color="#231151" label="3.5-4" opacity="1" quantity="16"/>' +
  '<ColorMapEntry color="#410F75" label="4-4.5" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#5F187F" label="4.5-5" opacity="1" quantity="18"/>' +
  '<ColorMapEntry color="#7B2382" label="5-5.7" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#982D80" label="5.7-6.4" opacity="1" quantity="20"/>' +
  '<ColorMapEntry color="#B63679" label="6.4-7.2" opacity="1" quantity="21"/>' +
  '<ColorMapEntry color="#D3436E" label="7.2-8" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#EB5760" label="8-9" opacity="1" quantity="23"/>' +
  '<ColorMapEntry color="#F8765C" label="9-10" opacity="1" quantity="24"/>' +
  '<ColorMapEntry color="#FD9969" label="10-11.2" opacity="1" quantity="25"/>' +
  '<ColorMapEntry color="#FEBA80" label="11.2-12.5" opacity="1" quantity="26"/>' +
  '<ColorMapEntry color="#FDDC9E" label="12.5-13.9" opacity="1" quantity="27"/>' +
  '<ColorMapEntry color="#FCFDBF" label="13.9-40" opacity="1" quantity="28"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var mean_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#000004" label="0-2.3" opacity="1" quantity="12"/>' +
  '<ColorMapEntry color="#0C0927" label="2.3-3.5" opacity="1" quantity="15"/>' +
  '<ColorMapEntry color="#231151" label="3.5-4" opacity="1" quantity="16"/>' +
  '<ColorMapEntry color="#410F75" label="4-4.5" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#5F187F" label="4.5-5" opacity="1" quantity="18"/>' +
  '<ColorMapEntry color="#7B2382" label="5-5.7" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#982D80" label="5.7-6.4" opacity="1" quantity="20"/>' +
  '<ColorMapEntry color="#B63679" label="6.4-7.2" opacity="1" quantity="21"/>' +
  '<ColorMapEntry color="#D3436E" label="7.2-8" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#EB5760" label="8-9" opacity="1" quantity="23"/>' +
  '<ColorMapEntry color="#F8765C" label="9-10" opacity="1" quantity="24"/>' +
  '<ColorMapEntry color="#FD9969" label="10-11.2" opacity="1" quantity="25"/>' +
  '<ColorMapEntry color="#FEBA80" label="11.2-12.5" opacity="1" quantity="26"/>' +
  '<ColorMapEntry color="#FDDC9E" label="12.5-13.9" opacity="1" quantity="27"/>' +
  '<ColorMapEntry color="#FCFDBF" label="13.9-40" opacity="1" quantity="28"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var stdev_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>' +
  '<ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>' +
  '<ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>' +
  '<ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>' +
  '<ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var stdev_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#fde725" label="low" opacity="1" quantity="1"/>' +
  '<ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="2"/>' +
  '<ColorMapEntry color="#20908d" label=" " opacity="1" quantity="3"/>' +
  '<ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="4"/>' +
  '<ColorMapEntry color="#440154" label="high" opacity="1" quantity="5"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var raw = ee.Image("ISDASOIL/Africa/v1/carbon_organic");
Map.addLayer(
    raw.select(0).sldStyle(mean_0_20), {},
    "Carbon, organic, mean visualization, 0-20 cm");
Map.addLayer(
    raw.select(1).sldStyle(mean_20_50), {},
    "Carbon, organic, mean visualization, 20-50 cm");
Map.addLayer(
    raw.select(2).sldStyle(stdev_0_20), {},
    "Carbon, organic, stdev visualization, 0-20 cm");
Map.addLayer(
    raw.select(3).sldStyle(stdev_20_50), {},
    "Carbon, organic, stdev visualization, 20-50 cm");

var converted = raw.divide(10).exp().subtract(1);

var visualization = {min: 0, max: 20};

Map.setCenter(25, -3, 2);

Map.addLayer(converted.select(0), visualization, "Carbon, organic, mean, 0-20 cm");