iSDAsoil Extractable Iron
संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
डेटासेट की उपलब्धता
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
डेटासेट उपलब्ध कराने वाली कंपनी
iSDA
Earth Engine स्निपेट
ee.Image("ISDASOIL/Africa/v1/iron_extractable")
open_in_new
टैग
africa
isda
soil
आयरन
ब्यौरा
मिट्टी की गहराई 0-20 सेमी और 20-50 सेमी पर, निकालने योग्य आयरन की मात्रा. अनुमानित माध्य और मानक विचलन.
पिक्सल वैल्यू को exp(x/10)-1 के साथ वापस बदलना होगा.
घने जंगल वाले इलाकों (आम तौर पर मध्य अफ़्रीका) में, मॉडल की सटीकता कम होती है. इसलिए, बैंडिंग (स्ट्राइपिंग) जैसे आर्टफ़ैक्ट दिख सकते हैं.
मिट्टी की प्रॉपर्टी के बारे में अनुमान, Innovative Solutions for Decision Agriculture Ltd. (iSDA) ने लगाए थे. इसके लिए, 30 मीटर पिक्सल साइज़ का इस्तेमाल किया गया था. साथ ही, रिमोट सेंसिंग डेटा के साथ मशीन लर्निंग का इस्तेमाल किया गया था. इसके अलावा, मिट्टी के 1,00,000 से ज़्यादा विश्लेषण किए गए सैंपल का ट्रेनिंग सेट भी इस्तेमाल किया गया था.
ज़्यादा जानकारी के लिए, अक्सर पूछे जाने वाले सवाल और तकनीकी जानकारी से जुड़े दस्तावेज़ पढ़ें. किसी समस्या की शिकायत करने या सहायता पाने का अनुरोध करने के लिए, कृपया iSDAsoil की साइट पर जाएं.
बैंड
पिक्सल का साइज़
बैंड
नाम
इकाइयां
कम से कम
ज़्यादा से ज़्यादा
पिक्सल का साइज़
ब्यौरा
mean_0_20ppm
0
62
मीटर
आयरन, निकालने योग्य, 0-20 सेमी की गहराई पर अनुमानित औसत
mean_20_50ppm
0
47
मीटर
आयरन, निकालने योग्य, 20-50 सेमी की गहराई पर अनुमानित औसत
stdev_0_20ppm
0
39
मीटर
आयरन, निकालने योग्य, 0 से 20 सेंटीमीटर की गहराई पर मानक विचलन
stdev_20_50ppm
0
39
मीटर
आयरन, निकालने योग्य, 20 से 50 सेंटीमीटर की गहराई पर मानक विचलन
उद्धरण
टॉम हेंगल, मिलर, एम॰ए॰ई॰, क्रिशनन, जे., वगैरह. अफ़्रीका की मिट्टी की प्रॉपर्टी और पोषक तत्वों को 30 मीटर के स्पेशल रिज़ॉल्यूशन पर मैप किया गया है. इसके लिए, दो-स्केल वाले एनसेंबल मशीन लर्निंग का इस्तेमाल किया गया है.
Sci Rep 11, 6130 (2021).
doi:10.1038/s41598-021-85639-y
Earth Engine की मदद से एक्सप्लोर करना
अहम जानकारी:
Earth Engine, पेटाबाइट-स्केल पर वैज्ञानिक विश्लेषण और भू-स्थानिक डेटासेट के विज़ुअलाइज़ेशन के लिए एक प्लैटफ़ॉर्म है. इसका इस्तेमाल, सार्वजनिक फ़ायदे के लिए तो होता ही है, इसे कारोबारी और सरकारी उपयोगकर्ता भी इस्तेमाल कर सकते हैं.
Earth Engine का इस्तेमाल रिसर्च, शिक्षा, और गैर-लाभकारी कामों के लिए बिना किसी शुल्क के किया जा सकता है. शुरू करने के लिए, कृपया Earth Engine को ऐक्सेस करने के लिए रजिस्टर करें.
कोड एडिटर (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" );
Open in Code Editor
[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)"]]
