iSDAsoil Extractable Iron
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
Veri Kümesi Kullanılabilirliği
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
Veri Kümesi Sağlayıcı
iSDA
Earth Engine Snippet
ee.Image("ISDASOIL/Africa/v1/iron_extractable")
open_in_new
Etiketler
africa
isda
soil
ütü yapma
Açıklama
0-20 cm ve 20-50 cm toprak derinliklerinde çıkarılabilir demir, tahmini ortalama ve standart sapma.
Piksel değerleri exp(x/10)-1 ile ters dönüştürülmelidir.
Yoğun ormanlık alanlarda (genellikle Orta Afrika'nın üzerinde) model doğruluğu düşüktür ve bu nedenle bantlama (şeritlenme) gibi yapaylıklar görülebilir.
Toprak özelliği tahminleri,uzaktan algılama verileri ve 100.000'den fazla analiz edilmiş toprak örneğinden oluşan bir eğitim setiyle birlikte makine öğrenimi kullanılarak 30 m piksel boyutunda Innovative Solutions for Decision Agriculture Ltd. (iSDA) tarafından yapılmıştır.
Daha fazla bilgiyi SSS ve teknik bilgi belgelerinde bulabilirsiniz. Sorun göndermek veya destek isteğinde bulunmak için lütfen iSDAsoil sitesini ziyaret edin.
Bantlar
Piksel Boyutu
Bantlar
Ad
Birimler
Min.
Maks.
Piksel Boyutu
Açıklama
mean_0_20ppm
0
62
metre
Demir, çıkarılabilir, 0-20 cm derinlikte tahmini ortalama
mean_20_50ppm
0
47
metre
Demir, ekstrakte edilebilir, 20-50 cm derinlikte tahmini ortalama
stdev_0_20ppm
0
39
metre
Demir, ekstrakte edilebilir, 0-20 cm derinlikte standart sapma
stdev_20_50ppm
0
39
metre
Demir, ekstrakte edilebilir, 20-50 cm derinlikte standart sapma
Kullanım Şartları
Kullanım Şartları
CC-BY-4.0
Alıntılar
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
Earth Engine ile keşfetme
Önemli:
Earth Engine, hem kamu yararı hem de işletme ve devlet kullanıcıları için petabayt ölçeğinde bilimsel analiz ve görselleştirme amacıyla kullanılan bir platformdur.
Earth Engine; araştırma, eğitim ve kâr amacı gütmeyen kuruluşlar için ücretsizdir. Başlamak için lütfen Earth Engine erişimi için kaydolun.
Kod Düzenleyici (JavaScript)
var mean_0_20 =
'<RasterSymbolizer>' +
'<ColorMap type="ramp">' +
'<ColorMapEntry color="#0D0887" label="0-6.4" opacity="1" quantity="20"/>' +
'<ColorMapEntry color="#350498" label="6.4-13.9" opacity="1" quantity="27"/>' +
'<ColorMapEntry color="#5402A3" label="13.9-29" opacity="1" quantity="34"/>' +
'<ColorMapEntry color="#7000A8" label="29-35.6" opacity="1" quantity="36"/>' +
'<ColorMapEntry color="#8B0AA5" label="35.6-43.7" opacity="1" quantity="38"/>' +
'<ColorMapEntry color="#A31E9A" label="43.7-48.4" opacity="1" quantity="39"/>' +
'<ColorMapEntry color="#B93289" label="48.4-53.6" opacity="1" quantity="40"/>' +
'<ColorMapEntry color="#CC4678" label="53.6-59.3" opacity="1" quantity="41"/>' +
'<ColorMapEntry color="#DB5C68" label="59.3-65.7" opacity="1" quantity="42"/>' +
'<ColorMapEntry color="#E97158" label="65.7-72.7" opacity="1" quantity="43"/>' +
'<ColorMapEntry color="#F48849" label="72.7-80.5" opacity="1" quantity="44"/>' +
'<ColorMapEntry color="#FBA139" label="80.5-89" opacity="1" quantity="45"/>' +
'<ColorMapEntry color="#FEBC2A" label="89-98.5" opacity="1" quantity="46"/>' +
'<ColorMapEntry color="#FADA24" label="98.5-108.9" opacity="1" quantity="47"/>' +
'<ColorMapEntry color="#F0F921" label="108.9-1200" opacity="1" quantity="48"/>' +
'</ColorMap>' +
'<ContrastEnhancement/>' +
'</RasterSymbolizer>' ;
var mean_20_50 =
'<RasterSymbolizer>' +
'<ColorMap type="ramp">' +
'<ColorMapEntry color="#0D0887" label="0-6.4" opacity="1" quantity="20"/>' +
'<ColorMapEntry color="#350498" label="6.4-13.9" opacity="1" quantity="27"/>' +
'<ColorMapEntry color="#5402A3" label="13.9-29" opacity="1" quantity="34"/>' +
'<ColorMapEntry color="#7000A8" label="29-35.6" opacity="1" quantity="36"/>' +
'<ColorMapEntry color="#8B0AA5" label="35.6-43.7" opacity="1" quantity="38"/>' +
'<ColorMapEntry color="#A31E9A" label="43.7-48.4" opacity="1" quantity="39"/>' +
'<ColorMapEntry color="#B93289" label="48.4-53.6" opacity="1" quantity="40"/>' +
'<ColorMapEntry color="#CC4678" label="53.6-59.3" opacity="1" quantity="41"/>' +
'<ColorMapEntry color="#DB5C68" label="59.3-65.7" opacity="1" quantity="42"/>' +
'<ColorMapEntry color="#E97158" label="65.7-72.7" opacity="1" quantity="43"/>' +
'<ColorMapEntry color="#F48849" label="72.7-80.5" opacity="1" quantity="44"/>' +
'<ColorMapEntry color="#FBA139" label="80.5-89" opacity="1" quantity="45"/>' +
'<ColorMapEntry color="#FEBC2A" label="89-98.5" opacity="1" quantity="46"/>' +
'<ColorMapEntry color="#FADA24" label="98.5-108.9" opacity="1" quantity="47"/>' +
'<ColorMapEntry color="#F0F921" label="108.9-1200" opacity="1" quantity="48"/>' +
'</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="6"/>' +
'</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="6"/>' +
'</ColorMap>' +
'<ContrastEnhancement/>' +
'</RasterSymbolizer>' ;
var raw = ee . Image ( "ISDASOIL/Africa/v1/iron_extractable" );
Map . addLayer (
raw . select ( 0 ). sldStyle ( mean_0_20 ), {},
"Iron, extractable, mean visualization, 0-20 cm" );
Map . addLayer (
raw . select ( 1 ). sldStyle ( mean_20_50 ), {},
"Iron, extractable, mean visualization, 20-50 cm" );
Map . addLayer (
raw . select ( 2 ). sldStyle ( stdev_0_20 ), {},
"Iron, extractable, stdev visualization, 0-20 cm" );
Map . addLayer (
raw . select ( 3 ). sldStyle ( stdev_20_50 ), {},
"Iron, extractable, stdev visualization, 20-50 cm" );
var converted = raw . divide ( 10 ). exp (). subtract ( 1 );
var visualization = { min : 0 , max : 140 };
Map . setCenter ( 25 , - 3 , 2 );
Map . addLayer ( converted . select ( 0 ), visualization , "Iron, extractable, mean, 0-20 cm" );
Kod Düzenleyici'de aç
[null,null,[],[[["\u003cp\u003eThis dataset provides the predicted mean and standard deviation of extractable iron 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 data.\u003c/p\u003e\n"],["\u003cp\u003ePixel values require back-transformation using the formula \u003ccode\u003eexp(x/10)-1\u003c/code\u003e for analysis.\u003c/p\u003e\n"],["\u003cp\u003eModel accuracy is lower in dense jungle areas, potentially leading to visual artifacts.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available under the CC-BY-4.0 license and users are encouraged to cite the relevant scientific publication.\u003c/p\u003e\n"]]],[],null,["# iSDAsoil Extractable Iron\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) \niron \n\n#### Description\n\nExtractable iron 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 | 0 | 62 | meters | Iron, extractable, predicted mean at 0-20 cm depth |\n| `mean_20_50` | ppm | 0 | 47 | meters | Iron, extractable, predicted mean at 20-50 cm depth |\n| `stdev_0_20` | ppm | 0 | 39 | meters | Iron, extractable, standard deviation at 0-20 cm depth |\n| `stdev_20_50` | ppm | 0 | 39 | meters | Iron, 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=\"0-6.4\" opacity=\"1\" quantity=\"20\"/\u003e' +\n '\u003cColorMapEntry color=\"#350498\" label=\"6.4-13.9\" opacity=\"1\" quantity=\"27\"/\u003e' +\n '\u003cColorMapEntry color=\"#5402A3\" label=\"13.9-29\" opacity=\"1\" quantity=\"34\"/\u003e' +\n '\u003cColorMapEntry color=\"#7000A8\" label=\"29-35.6\" opacity=\"1\" quantity=\"36\"/\u003e' +\n '\u003cColorMapEntry color=\"#8B0AA5\" label=\"35.6-43.7\" opacity=\"1\" quantity=\"38\"/\u003e' +\n '\u003cColorMapEntry color=\"#A31E9A\" label=\"43.7-48.4\" opacity=\"1\" quantity=\"39\"/\u003e' +\n '\u003cColorMapEntry color=\"#B93289\" label=\"48.4-53.6\" opacity=\"1\" quantity=\"40\"/\u003e' +\n '\u003cColorMapEntry color=\"#CC4678\" label=\"53.6-59.3\" opacity=\"1\" quantity=\"41\"/\u003e' +\n '\u003cColorMapEntry color=\"#DB5C68\" label=\"59.3-65.7\" opacity=\"1\" quantity=\"42\"/\u003e' +\n '\u003cColorMapEntry color=\"#E97158\" label=\"65.7-72.7\" opacity=\"1\" quantity=\"43\"/\u003e' +\n '\u003cColorMapEntry color=\"#F48849\" label=\"72.7-80.5\" opacity=\"1\" quantity=\"44\"/\u003e' +\n '\u003cColorMapEntry color=\"#FBA139\" label=\"80.5-89\" opacity=\"1\" quantity=\"45\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEBC2A\" label=\"89-98.5\" opacity=\"1\" quantity=\"46\"/\u003e' +\n '\u003cColorMapEntry color=\"#FADA24\" label=\"98.5-108.9\" opacity=\"1\" quantity=\"47\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0F921\" label=\"108.9-1200\" opacity=\"1\" quantity=\"48\"/\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=\"0-6.4\" opacity=\"1\" quantity=\"20\"/\u003e' +\n '\u003cColorMapEntry color=\"#350498\" label=\"6.4-13.9\" opacity=\"1\" quantity=\"27\"/\u003e' +\n '\u003cColorMapEntry color=\"#5402A3\" label=\"13.9-29\" opacity=\"1\" quantity=\"34\"/\u003e' +\n '\u003cColorMapEntry color=\"#7000A8\" label=\"29-35.6\" opacity=\"1\" quantity=\"36\"/\u003e' +\n '\u003cColorMapEntry color=\"#8B0AA5\" label=\"35.6-43.7\" opacity=\"1\" quantity=\"38\"/\u003e' +\n '\u003cColorMapEntry color=\"#A31E9A\" label=\"43.7-48.4\" opacity=\"1\" quantity=\"39\"/\u003e' +\n '\u003cColorMapEntry color=\"#B93289\" label=\"48.4-53.6\" opacity=\"1\" quantity=\"40\"/\u003e' +\n '\u003cColorMapEntry color=\"#CC4678\" label=\"53.6-59.3\" opacity=\"1\" quantity=\"41\"/\u003e' +\n '\u003cColorMapEntry color=\"#DB5C68\" label=\"59.3-65.7\" opacity=\"1\" quantity=\"42\"/\u003e' +\n '\u003cColorMapEntry color=\"#E97158\" label=\"65.7-72.7\" opacity=\"1\" quantity=\"43\"/\u003e' +\n '\u003cColorMapEntry color=\"#F48849\" label=\"72.7-80.5\" opacity=\"1\" quantity=\"44\"/\u003e' +\n '\u003cColorMapEntry color=\"#FBA139\" label=\"80.5-89\" opacity=\"1\" quantity=\"45\"/\u003e' +\n '\u003cColorMapEntry color=\"#FEBC2A\" label=\"89-98.5\" opacity=\"1\" quantity=\"46\"/\u003e' +\n '\u003cColorMapEntry color=\"#FADA24\" label=\"98.5-108.9\" opacity=\"1\" quantity=\"47\"/\u003e' +\n '\u003cColorMapEntry color=\"#F0F921\" label=\"108.9-1200\" opacity=\"1\" quantity=\"48\"/\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=\"6\"/\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=\"6\"/\u003e' +\n '\u003c/ColorMap\u003e' +\n '\u003cContrastEnhancement/\u003e' +\n'\u003c/RasterSymbolizer\u003e';\n\nvar raw = ee.Image(\"ISDASOIL/Africa/v1/iron_extractable\");\nMap.addLayer(\n raw.select(0).sldStyle(mean_0_20), {},\n \"Iron, extractable, mean visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(1).sldStyle(mean_20_50), {},\n \"Iron, extractable, mean visualization, 20-50 cm\");\nMap.addLayer(\n raw.select(2).sldStyle(stdev_0_20), {},\n \"Iron, extractable, stdev visualization, 0-20 cm\");\nMap.addLayer(\n raw.select(3).sldStyle(stdev_20_50), {},\n \"Iron, extractable, stdev visualization, 20-50 cm\");\n\nvar converted = raw.divide(10).exp().subtract(1);\n\nvar visualization = {min: 0, max: 140};\n\nMap.setCenter(25, -3, 2);\n\nMap.addLayer(converted.select(0), visualization, \"Iron, extractable, mean, 0-20 cm\");\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/ISDASOIL/ISDASOIL_Africa_v1_iron_extractable) \n[iSDAsoil Extractable Iron](/earth-engine/datasets/catalog/ISDASOIL_Africa_v1_iron_extractable) \nExtractable iron 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/iron_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_iron_extractable)"]]
