iSDAsoil Extractable Calcium
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Disponibilità del set di dati
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
Fornitore di set di dati
iSDA
Snippet di Earth Engine
ee.Image("ISDASOIL/Africa/v1/calcium_extractable")
open_in_new
Tag
africa
isda
soil
calcio
Descrizione
Calcio estraibile a profondità del suolo di 0-20 cm e 20-50 cm,
media e deviazione standard previste.
I valori dei pixel devono essere trasformati nuovamente con exp(x/10)-1.
Nelle aree di giungla fitta (generalmente nell'Africa centrale), l'accuratezza del modello è
bassa e pertanto potrebbero essere visibili artefatti come bande (strisce).
Le previsioni sulle proprietà del suolo sono state effettuate da
Innovative Solutions for Decision Agriculture Ltd. (iSDA)
con dimensioni dei pixel di 30 m utilizzando il machine learning combinato con dati di telerilevamento
e un set di addestramento di oltre 100.000 campioni di suolo analizzati.
Per ulteriori informazioni, consulta le
domande frequenti e la
documentazione sulle informazioni tecniche . Per segnalare un problema o richiedere assistenza, visita
il sito iSDAsoil .
Bande
Dimensioni pixel
Bande
Nome
Unità
Min
Max
Dimensioni dei pixel
Descrizione
mean_0_20ppm
20
100
metri
Calcio estraibile, media prevista a una profondità di 0-20 cm
mean_20_50ppm
14
100
metri
Calcio estraibile, media prevista a una profondità di 20-50 cm
stdev_0_20ppm
0
62
metri
Calcio estraibile, deviazione standard a una profondità di 0-20 cm
stdev_20_50ppm
0
63
metri
Calcio estraibile, deviazione standard a una profondità di 20-50 cm
Termini e condizioni d'uso
Termini e condizioni d'uso
CC-BY-4.0
Citazioni
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
Esplorare con Earth Engine
Importante:
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set di dati geospaziali, sia per il bene pubblico sia per gli utenti aziendali e governativi.
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Editor di codice (JavaScript)
var mean_0_20 =
'<RasterSymbolizer>' +
'<ColorMap type="ramp">' +
'<ColorMapEntry color="#0D0887" label="0-65.7" opacity="1" quantity="42"/>' +
'<ColorMapEntry color="#350498" label="65.7-120.5" opacity="1" quantity="48"/>' +
'<ColorMapEntry color="#5402A3" label="120.5-163" opacity="1" quantity="51"/>' +
'<ColorMapEntry color="#7000A8" label="163-199.3" opacity="1" quantity="53"/>' +
'<ColorMapEntry color="#8B0AA5" label="199.3-269.4" opacity="1" quantity="56"/>' +
'<ColorMapEntry color="#A31E9A" label="269.4-329.3" opacity="1" quantity="58"/>' +
'<ColorMapEntry color="#B93289" label="329.3-402.4" opacity="1" quantity="60"/>' +
'<ColorMapEntry color="#CC4678" label="402.4-491.7" opacity="1" quantity="62"/>' +
'<ColorMapEntry color="#DB5C68" label="491.7-600.8" opacity="1" quantity="64"/>' +
'<ColorMapEntry color="#E97158" label="600.8-664.1" opacity="1" quantity="65"/>' +
'<ColorMapEntry color="#F48849" label="664.1-811.4" opacity="1" quantity="67"/>' +
'<ColorMapEntry color="#FBA139" label="811.4-896.8" opacity="1" quantity="68"/>' +
'<ColorMapEntry color="#FEBC2A" label="896.8-1095.6" opacity="1" quantity="70"/>' +
'<ColorMapEntry color="#FADA24" label="1095.6-1479.3" opacity="1" quantity="73"/>' +
'<ColorMapEntry color="#F0F921" label="1479.3-12000" opacity="1" quantity="77"/>' +
'</ColorMap>' +
'<ContrastEnhancement/>' +
'</RasterSymbolizer>' ;
var mean_20_50 =
'<RasterSymbolizer>' +
'<ColorMap type="ramp">' +
'<ColorMapEntry color="#0D0887" label="0-65.7" opacity="1" quantity="42"/>' +
'<ColorMapEntry color="#350498" label="65.7-120.5" opacity="1" quantity="48"/>' +
'<ColorMapEntry color="#5402A3" label="120.5-163" opacity="1" quantity="51"/>' +
'<ColorMapEntry color="#7000A8" label="163-199.3" opacity="1" quantity="53"/>' +
'<ColorMapEntry color="#8B0AA5" label="199.3-269.4" opacity="1" quantity="56"/>' +
'<ColorMapEntry color="#A31E9A" label="269.4-329.3" opacity="1" quantity="58"/>' +
'<ColorMapEntry color="#B93289" label="329.3-402.4" opacity="1" quantity="60"/>' +
'<ColorMapEntry color="#CC4678" label="402.4-491.7" opacity="1" quantity="62"/>' +
'<ColorMapEntry color="#DB5C68" label="491.7-600.8" opacity="1" quantity="64"/>' +
'<ColorMapEntry color="#E97158" label="600.8-664.1" opacity="1" quantity="65"/>' +
'<ColorMapEntry color="#F48849" label="664.1-811.4" opacity="1" quantity="67"/>' +
'<ColorMapEntry color="#FBA139" label="811.4-896.8" opacity="1" quantity="68"/>' +
'<ColorMapEntry color="#FEBC2A" label="896.8-1095.6" opacity="1" quantity="70"/>' +
'<ColorMapEntry color="#FADA24" label="1095.6-1479.3" opacity="1" quantity="73"/>' +
'<ColorMapEntry color="#F0F921" label="1479.3-12000" opacity="1" quantity="77"/>' +
'</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/calcium_extractable" );
Map . addLayer (
raw . select ( 0 ). sldStyle ( mean_0_20 ), {},
"Calcium, extractable, mean visualization, 0-20 cm" );
Map . addLayer (
raw . select ( 1 ). sldStyle ( mean_20_50 ), {},
"Calcium, extractable, mean visualization, 20-50 cm" );
Map . addLayer (
raw . select ( 2 ). sldStyle ( stdev_0_20 ), {},
"Calcium, extractable, stdev visualization, 0-20 cm" );
Map . addLayer (
raw . select ( 3 ). sldStyle ( stdev_20_50 ), {},
"Calcium, extractable, stdev visualization, 20-50 cm" );
var converted = raw . divide ( 10 ). exp (). subtract ( 1 );
var visualization = { min : 100 , max : 2000 };
Map . setCenter ( 25 , - 3 , 2 );
Map . addLayer ( converted . select ( 0 ), visualization , "Calcium, extractable, mean, 0-20 cm" );
Apri nell'editor di codice
[null,null,[],[[["\u003cp\u003eThis dataset provides the predicted mean and standard deviation of extractable calcium in African soil at two depths (0-20 cm and 20-50 cm).\u003c/p\u003e\n"],["\u003cp\u003eThe data covers the period from 2001 to 2017 and was produced by iSDA using machine learning and remote sensing.\u003c/p\u003e\n"],["\u003cp\u003ePixel values require back-transformation using the formula \u003ccode\u003eexp(x/10)-1\u003c/code\u003e to obtain actual calcium concentrations in ppm.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset has a 30-meter resolution and may exhibit lower accuracy in dense jungle regions of central Africa.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access this dataset through Google Earth Engine and are encouraged to consult the provided resources for detailed information and support.\u003c/p\u003e\n"]]],[],null,["# iSDAsoil Extractable Calcium\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) \ncalcium \n\n#### Description\n\nExtractable calcium at soil depths of 0-20 cm and 20-50 cm,\npredicted mean and standard deviation.\n\nPixel values must be back-transformed with `exp(x/10)-1`.\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` | ppm | 20 | 100 | meters | Calcium, extractable, predicted mean at 0-20 cm depth |\n| `mean_20_50` | ppm | 14 | 100 | meters | Calcium, extractable, predicted mean at 20-50 cm depth |\n| `stdev_0_20` | ppm | 0 | 62 | meters | Calcium, extractable, standard deviation at 0-20 cm depth |\n| `stdev_20_50` | ppm | 0 | 63 | meters | Calcium, extractable, 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=\"#0D0887\" label=\"0-65.7\" opacity=\"1\" quantity=\"42\"/\u003e' +\n '\u003cColorMapEntry color=\"#350498\" label=\"65.7-120.5\" opacity=\"1\" quantity=\"48\"/\u003e' +\n '\u003cColorMapEntry color=\"#5402A3\" label=\"120.5-163\" opacity=\"1\" quantity=\"51\"/\u003e' +\n '\u003cColorMapEntry color=\"#7000A8\" label=\"163-199.3\" opacity=\"1\" quantity=\"53\"/\u003e' +\n '\u003cColorMapEntry color=\"#8B0AA5\" label=\"199.3-269.4\" opacity=\"1\" quantity=\"56\"/\u003e' +\n '\u003cColorMapEntry color=\"#A31E9A\" label=\"269.4-329.3\" opacity=\"1\" quantity=\"58\"/\u003e' +\n '\u003cColorMapEntry color=\"#B93289\" label=\"329.3-402.4\" opacity=\"1\" quantity=\"60\"/\u003e' +\n '\u003cColorMapEntry color=\"#CC4678\" label=\"402.4-491.7\" opacity=\"1\" quantity=\"62\"/\u003e' +\n '\u003cColorMapEntry color=\"#DB5C68\" label=\"491.7-600.8\" opacity=\"1\" quantity=\"64\"/\u003e' +\n '\u003cColorMapEntry color=\"#E97158\" label=\"600.8-664.1\" opacity=\"1\" quantity=\"65\"/\u003e' +\n '\u003cColorMapEntry color=\"#F48849\" label=\"664.1-811.4\" opacity=\"1\" quantity=\"67\"/\u003e' +\n '\u003cColorMapEntry color=\"#FBA139\" label=\"811.4-896.8\" opacity=\"1\" quantity=\"68\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEBC2A\" label=\"896.8-1095.6\" opacity=\"1\" quantity=\"70\"/\u003e' +\n '\u003cColorMapEntry color=\"#FADA24\" label=\"1095.6-1479.3\" opacity=\"1\" quantity=\"73\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0F921\" label=\"1479.3-12000\" opacity=\"1\" quantity=\"77\"/\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=\"#0D0887\" label=\"0-65.7\" opacity=\"1\" quantity=\"42\"/\u003e' +\n '\u003cColorMapEntry color=\"#350498\" label=\"65.7-120.5\" opacity=\"1\" quantity=\"48\"/\u003e' +\n '\u003cColorMapEntry color=\"#5402A3\" label=\"120.5-163\" opacity=\"1\" quantity=\"51\"/\u003e' +\n '\u003cColorMapEntry color=\"#7000A8\" label=\"163-199.3\" opacity=\"1\" quantity=\"53\"/\u003e' +\n '\u003cColorMapEntry color=\"#8B0AA5\" label=\"199.3-269.4\" opacity=\"1\" quantity=\"56\"/\u003e' +\n '\u003cColorMapEntry color=\"#A31E9A\" label=\"269.4-329.3\" opacity=\"1\" quantity=\"58\"/\u003e' +\n '\u003cColorMapEntry color=\"#B93289\" label=\"329.3-402.4\" opacity=\"1\" quantity=\"60\"/\u003e' +\n '\u003cColorMapEntry color=\"#CC4678\" label=\"402.4-491.7\" opacity=\"1\" quantity=\"62\"/\u003e' +\n '\u003cColorMapEntry color=\"#DB5C68\" label=\"491.7-600.8\" opacity=\"1\" quantity=\"64\"/\u003e' +\n '\u003cColorMapEntry color=\"#E97158\" label=\"600.8-664.1\" opacity=\"1\" quantity=\"65\"/\u003e' +\n '\u003cColorMapEntry color=\"#F48849\" label=\"664.1-811.4\" opacity=\"1\" quantity=\"67\"/\u003e' +\n '\u003cColorMapEntry color=\"#FBA139\" label=\"811.4-896.8\" opacity=\"1\" quantity=\"68\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEBC2A\" label=\"896.8-1095.6\" opacity=\"1\" quantity=\"70\"/\u003e' +\n '\u003cColorMapEntry color=\"#FADA24\" label=\"1095.6-1479.3\" opacity=\"1\" quantity=\"73\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0F921\" label=\"1479.3-12000\" opacity=\"1\" quantity=\"77\"/\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=\"1\"/\u003e' +\n '\u003cColorMapEntry color=\"#5dc962\" label=\" \" opacity=\"1\" quantity=\"2\"/\u003e' +\n '\u003cColorMapEntry color=\"#20908d\" label=\" \" opacity=\"1\" quantity=\"3\"/\u003e' +\n '\u003cColorMapEntry color=\"#3a528b\" label=\" \" opacity=\"1\" quantity=\"4\"/\u003e' +\n '\u003cColorMapEntry color=\"#440154\" label=\"high\" opacity=\"1\" quantity=\"5\"/\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=\"1\"/\u003e' +\n '\u003cColorMapEntry color=\"#5dc962\" label=\" \" opacity=\"1\" quantity=\"2\"/\u003e' +\n '\u003cColorMapEntry color=\"#20908d\" label=\" \" opacity=\"1\" quantity=\"3\"/\u003e' +\n '\u003cColorMapEntry color=\"#3a528b\" label=\" \" opacity=\"1\" quantity=\"4\"/\u003e' +\n '\u003cColorMapEntry color=\"#440154\" label=\"high\" opacity=\"1\" quantity=\"5\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar raw = ee.Image(\"ISDASOIL/Africa/v1/calcium_extractable\");\nMap.addLayer(\n raw.select(0).sldStyle(mean_0_20), {},\n \"Calcium, extractable, mean visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(1).sldStyle(mean_20_50), {},\n \"Calcium, extractable, mean visualization, 20-50 cm\");\nMap.addLayer(\n raw.select(2).sldStyle(stdev_0_20), {},\n \"Calcium, extractable, stdev visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(3).sldStyle(stdev_20_50), {},\n \"Calcium, extractable, stdev visualization, 20-50 cm\");\n\nvar converted = raw.divide(10).exp().subtract(1);\n\nvar visualization = {min: 100, max: 2000};\n\nMap.setCenter(25, -3, 2);\n\nMap.addLayer(converted.select(0), visualization, \"Calcium, extractable, mean, 0-20 cm\");\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/ISDASOIL/ISDASOIL_Africa_v1_calcium_extractable) \n[iSDAsoil Extractable Calcium](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_calcium_extractable) \nExtractable calcium 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 artifacts such as banding (striping) might be seen. Soil property predictions were ... \nISDASOIL/Africa/v1/calcium_extractable, 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_calcium_extractable)"]]
