iSDAsoil Bulk Density, <2mm Fraction

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

Description

Bulk density, <2mm fraction at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation.

Pixel values must be back-transformed with x/100.

In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts 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/cm^3 44 197

Bulk density, <2mm fraction, predicted mean at 0-20 cm depth
mean_20_50 g/cm^3 44 196

Bulk density, <2mm fraction, predicted mean at 20-50 cm depth
stdev_0_20 g/cm^3 0 92

Bulk density, <2mm fraction, standard deviation at 0-20 cm depth
stdev_20_50 g/cm^3 0 92

Bulk density, <2mm fraction, 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 with Earth Engine

Code Editor (JavaScript)

var mean_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0.8-1.05" opacity="1" quantity="105"/>' +
  '<ColorMapEntry color="#002D6C" label="1.05-1.19" opacity="1" quantity="119"/>' +
  '<ColorMapEntry color="#16396D" label="1.19-1.23" opacity="1" quantity="123"/>' +
  '<ColorMapEntry color="#36476B" label="1.23-1.25" opacity="1" quantity="125"/>' +
  '<ColorMapEntry color="#4B546C" label="1.25-1.28" opacity="1" quantity="128"/>' +
  '<ColorMapEntry color="#5C616E" label="1.28-1.31" opacity="1" quantity="131"/>' +
  '<ColorMapEntry color="#6C6E72" label="1.31-1.34" opacity="1" quantity="134"/>' +
  '<ColorMapEntry color="#7C7B78" label="1.34-1.36" opacity="1" quantity="136"/>' +
  '<ColorMapEntry color="#8E8A79" label="1.36-1.38" opacity="1" quantity="138"/>' +
  '<ColorMapEntry color="#A09877" label="1.38-1.41" opacity="1" quantity="141"/>' +
  '<ColorMapEntry color="#B3A772" label="1.41-1.43" opacity="1" quantity="143"/>' +
  '<ColorMapEntry color="#C6B66B" label="1.43-1.45" opacity="1" quantity="145"/>' +
  '<ColorMapEntry color="#DBC761" label="1.45-1.48" opacity="1" quantity="148"/>' +
  '<ColorMapEntry color="#F0D852" label="1.48-1.51" opacity="1" quantity="151"/>' +
  '<ColorMapEntry color="#FFEA46" label="1.51-1.85" opacity="1" quantity="154"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var mean_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0.8-1.05" opacity="1" quantity="105"/>' +
  '<ColorMapEntry color="#002D6C" label="1.05-1.19" opacity="1" quantity="119"/>' +
  '<ColorMapEntry color="#16396D" label="1.19-1.23" opacity="1" quantity="123"/>' +
  '<ColorMapEntry color="#36476B" label="1.23-1.25" opacity="1" quantity="125"/>' +
  '<ColorMapEntry color="#4B546C" label="1.25-1.28" opacity="1" quantity="128"/>' +
  '<ColorMapEntry color="#5C616E" label="1.28-1.31" opacity="1" quantity="131"/>' +
  '<ColorMapEntry color="#6C6E72" label="1.31-1.34" opacity="1" quantity="134"/>' +
  '<ColorMapEntry color="#7C7B78" label="1.34-1.36" opacity="1" quantity="136"/>' +
  '<ColorMapEntry color="#8E8A79" label="1.36-1.38" opacity="1" quantity="138"/>' +
  '<ColorMapEntry color="#A09877" label="1.38-1.41" opacity="1" quantity="141"/>' +
  '<ColorMapEntry color="#B3A772" label="1.41-1.43" opacity="1" quantity="143"/>' +
  '<ColorMapEntry color="#C6B66B" label="1.43-1.45" opacity="1" quantity="145"/>' +
  '<ColorMapEntry color="#DBC761" label="1.45-1.48" opacity="1" quantity="148"/>' +
  '<ColorMapEntry color="#F0D852" label="1.48-1.51" opacity="1" quantity="151"/>' +
  '<ColorMapEntry color="#FFEA46" label="1.51-1.85" opacity="1" quantity="154"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var stdev_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>' +
  '<ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="4"/>' +
  '<ColorMapEntry color="#20908d" label=" " opacity="1" quantity="5"/>' +
  '<ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="7"/>' +
  '<ColorMapEntry color="#440154" label="high" opacity="1" quantity="9"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var stdev_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#fde725" label="low" opacity="1" quantity="2"/>' +
  '<ColorMapEntry color="#5dc962" label=" " opacity="1" quantity="4"/>' +
  '<ColorMapEntry color="#20908d" label=" " opacity="1" quantity="5"/>' +
  '<ColorMapEntry color="#3a528b" label=" " opacity="1" quantity="7"/>' +
  '<ColorMapEntry color="#440154" label="high" opacity="1" quantity="9"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

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

var converted = raw.divide(100);

var visualization = {min: 1, max: 1.5};

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

Map.addLayer(converted.select(0), visualization, "Bulk density, mean, 0-20 cm");
Bulk density, <2mm fraction at soil depths of 0-20 cm and 20-50 cm, predicted mean and standard deviation. Pixel values must be back-transformed with x/100. In areas of dense jungle (generally over central Africa), model accuracy is low and therefore artifacts such as banding (striping) might be seen. Soil property …
ISDASOIL/Africa/v1/bulk_density, africa,isda,soil
2001-01-01T00:00:00Z/2017-01-01T00:00:00
-35.22 -31.46 37.98 57.08
Google Earth Engine