iSDAsoil Bulk Density, <2mm Fraction
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Disponibilité des ensembles de données
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
Fournisseur de l'ensemble de données
iSDA
Extrait Earth Engine
ee.Image("ISDASOIL/Africa/v1/bulk_density")
open_in_new
Tags
africa
isda
soil
masse volumique apparente
Description
Densité apparente, fraction <2 mm à des profondeurs de sol de 0 à 20 cm et de 20 à 50 cm, moyenne et écart-type prévus.
Les valeurs de pixels doivent être retransformées avec x/100.
Dans les zones de jungle dense (généralement en Afrique centrale), la précision du modèle est faible. Des artefacts tels que des bandes (rayures) peuvent donc apparaître.
Les prédictions des propriétés du sol ont été effectuées par Innovative Solutions for Decision Agriculture Ltd. (iSDA) à une taille de pixel de 30 mètres à l'aide du machine learning associé à des données de télédétection et d'un ensemble d'entraînement de plus de 100 000 échantillons de sol analysés.
Pour en savoir plus, consultez les questions fréquentes et la documentation sur les informations techniques . Pour signaler un problème ou demander de l'aide, veuillez consulter le site iSDAsoil .
Bracelets
Taille des pixels
Bandes de fréquences
Nom
Unités
Min
Max
Taille des pixels
Description
mean_0_20g/cm^3
44
197
mètres
Densité apparente, fraction <2 mm, moyenne prévue à une profondeur de 0 à 20 cm
mean_20_50g/cm^3
44
196
mètres
Densité apparente, fraction <2 mm, moyenne prévue à une profondeur de 20 à 50 cm
stdev_0_20g/cm^3
0
92
mètres
Densité apparente, fraction <2 mm, écart-type à une profondeur de 0 à 20 cm
stdev_20_50g/cm^3
0
92
mètres
Écart-type de la masse volumique apparente, fraction < 2 mm, à une profondeur de 20 à 50 cm
Conditions d'utilisation
Conditions d'utilisation
CC-BY-4.0
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
Explorer avec Earth Engine
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Earth Engine est un outil sans frais pour la recherche, l'enseignement et les organisations à but non lucratif. Pour commencer, veuillez demander l'accès à Earth Engine .
Éditeur de code (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" );
Ouvrir dans l'éditeur de code
[null,null,[],[[["\u003cp\u003eThis dataset provides soil bulk density data for Africa at 30-meter resolution, covering the period from 2001 to 2017.\u003c/p\u003e\n"],["\u003cp\u003eIt includes predicted mean and standard deviation of bulk density for soil depths of 0-20 cm and 20-50 cm.\u003c/p\u003e\n"],["\u003cp\u003eThe data is derived from machine learning models trained on over 100,000 soil samples and remote sensing data, with potential for lower accuracy in dense jungle areas.\u003c/p\u003e\n"],["\u003cp\u003ePixel values require back-transformation by dividing by 100 to obtain the actual bulk density in g/cm³.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is provided by Innovative Solutions for Decision Agriculture Ltd.(iSDA) under a CC-BY-4.0 license.\u003c/p\u003e\n"]]],[],null,["# iSDAsoil Bulk Density, <2mm Fraction\n\nDataset Availability\n: 2001-01-01T00:00:00Z--2017-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [iSDA](https://isda-africa.com/)\n\nTags\n:\n [africa](/earth-engine/datasets/tags/africa) [isda](/earth-engine/datasets/tags/isda) [soil](/earth-engine/datasets/tags/soil) \nbulk-density \n\n#### Description\n\nBulk density, \\\u003c2mm fraction at soil depths of 0-20 cm and 20-50 cm,\npredicted mean and standard deviation.\n\nPixel values must be back-transformed with `x/100`.\n\nIn areas of dense jungle (generally over central Africa), model accuracy is\nlow and therefore artifacts such as banding (striping) might be seen.\n\nSoil property predictions were made by\n[Innovative Solutions for Decision Agriculture Ltd. (iSDA)](https://isda-africa.com/)\nat 30 m pixel size using machine learning coupled with remote sensing data\nand a training set of over 100,000 analyzed soil samples.\n\nFurther information can be found in the\n[FAQ](https://www.isda-africa.com/isdasoil/faq/) and\n[technical information documentation](https://www.isda-africa.com/isdasoil/technical-information/). To submit an issue or request support, please visit\n[the iSDAsoil site](https://isda-africa.com/isdasoil).\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|---------------|---------|-----|-----|------------|--------------------------------------------------------------------|\n| `mean_0_20` | g/cm\\^3 | 44 | 197 | meters | Bulk density, \\\u003c2mm fraction, predicted mean at 0-20 cm depth |\n| `mean_20_50` | g/cm\\^3 | 44 | 196 | meters | Bulk density, \\\u003c2mm fraction, predicted mean at 20-50 cm depth |\n| `stdev_0_20` | g/cm\\^3 | 0 | 92 | meters | Bulk density, \\\u003c2mm fraction, standard deviation at 0-20 cm depth |\n| `stdev_20_50` | g/cm\\^3 | 0 | 92 | meters | Bulk density, \\\u003c2mm fraction, standard deviation at 20-50 cm depth |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- Hengl, T., Miller, M.A.E., Križan, J., et al. African soil properties and nutrients\n mapped at 30 m spatial resolution using two-scale ensemble machine learning.\n Sci Rep 11, 6130 (2021).\n [doi:10.1038/s41598-021-85639-y](https://doi.org/10.1038/s41598-021-85639-y)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar mean_0_20 =\n'\u003cRasterSymbolizer\u003e' +\n '\u003cColorMap type=\"ramp\"\u003e' +\n '\u003cColorMapEntry color=\"#00204D\" label=\"0.8-1.05\" opacity=\"1\" quantity=\"105\"/\u003e' +\n '\u003cColorMapEntry color=\"#002D6C\" label=\"1.05-1.19\" opacity=\"1\" quantity=\"119\"/\u003e' +\n '\u003cColorMapEntry color=\"#16396D\" label=\"1.19-1.23\" opacity=\"1\" quantity=\"123\"/\u003e' +\n '\u003cColorMapEntry color=\"#36476B\" label=\"1.23-1.25\" opacity=\"1\" quantity=\"125\"/\u003e' +\n '\u003cColorMapEntry color=\"#4B546C\" label=\"1.25-1.28\" opacity=\"1\" quantity=\"128\"/\u003e' +\n '\u003cColorMapEntry color=\"#5C616E\" label=\"1.28-1.31\" opacity=\"1\" quantity=\"131\"/\u003e' +\n '\u003cColorMapEntry color=\"#6C6E72\" label=\"1.31-1.34\" opacity=\"1\" quantity=\"134\"/\u003e' +\n '\u003cColorMapEntry color=\"#7C7B78\" label=\"1.34-1.36\" opacity=\"1\" quantity=\"136\"/\u003e' +\n '\u003cColorMapEntry color=\"#8E8A79\" label=\"1.36-1.38\" opacity=\"1\" quantity=\"138\"/\u003e' +\n '\u003cColorMapEntry color=\"#A09877\" label=\"1.38-1.41\" opacity=\"1\" quantity=\"141\"/\u003e' +\n '\u003cColorMapEntry color=\"#B3A772\" label=\"1.41-1.43\" opacity=\"1\" quantity=\"143\"/\u003e' +\n '\u003cColorMapEntry color=\"#C6B66B\" label=\"1.43-1.45\" opacity=\"1\" quantity=\"145\"/\u003e' +\n '\u003cColorMapEntry color=\"#DBC761\" label=\"1.45-1.48\" opacity=\"1\" quantity=\"148\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0D852\" label=\"1.48-1.51\" opacity=\"1\" quantity=\"151\"/\u003e' +\n '\u003cColorMapEntry color=\"#FFEA46\" label=\"1.51-1.85\" opacity=\"1\" quantity=\"154\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar mean_20_50 =\n'\u003cRasterSymbolizer\u003e' +\n '\u003cColorMap type=\"ramp\"\u003e' +\n '\u003cColorMapEntry color=\"#00204D\" label=\"0.8-1.05\" opacity=\"1\" quantity=\"105\"/\u003e' +\n '\u003cColorMapEntry color=\"#002D6C\" label=\"1.05-1.19\" opacity=\"1\" quantity=\"119\"/\u003e' +\n '\u003cColorMapEntry color=\"#16396D\" label=\"1.19-1.23\" opacity=\"1\" quantity=\"123\"/\u003e' +\n '\u003cColorMapEntry color=\"#36476B\" label=\"1.23-1.25\" opacity=\"1\" quantity=\"125\"/\u003e' +\n '\u003cColorMapEntry color=\"#4B546C\" label=\"1.25-1.28\" opacity=\"1\" quantity=\"128\"/\u003e' +\n '\u003cColorMapEntry color=\"#5C616E\" label=\"1.28-1.31\" opacity=\"1\" quantity=\"131\"/\u003e' +\n '\u003cColorMapEntry color=\"#6C6E72\" label=\"1.31-1.34\" opacity=\"1\" quantity=\"134\"/\u003e' +\n '\u003cColorMapEntry color=\"#7C7B78\" label=\"1.34-1.36\" opacity=\"1\" quantity=\"136\"/\u003e' +\n '\u003cColorMapEntry color=\"#8E8A79\" label=\"1.36-1.38\" opacity=\"1\" quantity=\"138\"/\u003e' +\n '\u003cColorMapEntry color=\"#A09877\" label=\"1.38-1.41\" opacity=\"1\" quantity=\"141\"/\u003e' +\n '\u003cColorMapEntry color=\"#B3A772\" label=\"1.41-1.43\" opacity=\"1\" quantity=\"143\"/\u003e' +\n '\u003cColorMapEntry color=\"#C6B66B\" label=\"1.43-1.45\" opacity=\"1\" quantity=\"145\"/\u003e' +\n '\u003cColorMapEntry color=\"#DBC761\" label=\"1.45-1.48\" opacity=\"1\" quantity=\"148\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0D852\" label=\"1.48-1.51\" opacity=\"1\" quantity=\"151\"/\u003e' +\n '\u003cColorMapEntry color=\"#FFEA46\" label=\"1.51-1.85\" opacity=\"1\" quantity=\"154\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar stdev_0_20 =\n'\u003cRasterSymbolizer\u003e' +\n '\u003cColorMap type=\"ramp\"\u003e' +\n '\u003cColorMapEntry color=\"#fde725\" label=\"low\" opacity=\"1\" quantity=\"2\"/\u003e' +\n '\u003cColorMapEntry color=\"#5dc962\" label=\" \" opacity=\"1\" quantity=\"4\"/\u003e' +\n '\u003cColorMapEntry color=\"#20908d\" label=\" \" opacity=\"1\" quantity=\"5\"/\u003e' +\n '\u003cColorMapEntry color=\"#3a528b\" label=\" \" opacity=\"1\" quantity=\"7\"/\u003e' +\n '\u003cColorMapEntry color=\"#440154\" label=\"high\" opacity=\"1\" quantity=\"9\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar stdev_20_50 =\n'\u003cRasterSymbolizer\u003e' +\n '\u003cColorMap type=\"ramp\"\u003e' +\n '\u003cColorMapEntry color=\"#fde725\" label=\"low\" opacity=\"1\" quantity=\"2\"/\u003e' +\n '\u003cColorMapEntry color=\"#5dc962\" label=\" \" opacity=\"1\" quantity=\"4\"/\u003e' +\n '\u003cColorMapEntry color=\"#20908d\" label=\" \" opacity=\"1\" quantity=\"5\"/\u003e' +\n '\u003cColorMapEntry color=\"#3a528b\" label=\" \" opacity=\"1\" quantity=\"7\"/\u003e' +\n '\u003cColorMapEntry color=\"#440154\" label=\"high\" opacity=\"1\" quantity=\"9\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar raw = ee.Image(\"ISDASOIL/Africa/v1/bulk_density\");\nMap.addLayer(\n raw.select(0).sldStyle(mean_0_20), {},\n \"Bulk density, mean visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(1).sldStyle(mean_20_50), {},\n \"Bulk density, mean visualization, 20-50 cm\");\nMap.addLayer(\n raw.select(2).sldStyle(stdev_0_20), {},\n \"Bulk density, stdev visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(3).sldStyle(stdev_20_50), {},\n \"Bulk density, stdev visualization, 20-50 cm\");\n\nvar converted = raw.divide(100);\n\nvar visualization = {min: 1, max: 1.5};\n\nMap.setCenter(25, -3, 2);\n\nMap.addLayer(converted.select(0), visualization, \"Bulk density, mean, 0-20 cm\");\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/ISDASOIL/ISDASOIL_Africa_v1_bulk_density) \n[iSDAsoil Bulk Density, \\\u003c2mm Fraction](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_bulk_density) \nBulk density, \\\u003c2mm 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 ... \nISDASOIL/Africa/v1/bulk_density, africa,isda,soil \n2001-01-01T00:00:00Z/2017-01-01T00:00:00Z \n-35.22 -31.46 37.98 57.08 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://isda-africa.com/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_bulk_density)"]]
