iSDAsoil Silt Content

ISDASOIL/Africa/v1/silt_content
資料集可用性
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
資料集來源
Earth Engine 程式碼片段
ee.Image("ISDASOIL/Africa/v1/silt_content")
標記
africa isda soil
Silt

說明

土壤深度 0-20 公分和 20-50 公分的粉土含量、預測平均值和標準差。

像素值必須使用 exp(x/10)-1 進行反向轉換。

在叢林密布的區域 (通常位於中非),模型準確度較低,因此可能會出現帶狀 (條紋) 等構件。

土壤性質預測是由 Innovative Solutions for Decision Agriculture Ltd. (iSDA) 進行,採用機器學習技術搭配遙測資料,以及超過 10 萬個分析過的土壤樣本訓練集,以 30 公尺的像素大小進行預測。

詳情請參閱常見問題技術資訊說明文件。如要提交問題或要求支援,請前往iSDAsoil 網站

頻帶

像素大小
30 公尺

頻帶

名稱 單位 最小值 最大值 像素大小 說明
mean_0_20 % 1 61 公尺

粉土含量,預測平均值 (深度 0 到 20 公分)

mean_20_50 % 0 62 公尺

粉土含量,預測平均深度為 20 至 50 公分

stdev_0_20 % 0 38 公尺

粉土含量,0 到 20 公分深度的標準差

stdev_20_50 % 0 38 公尺

粉土含量,20 至 50 公分深度的標準差

使用條款

使用條款

CC-BY-4.0

引用內容

引用內容:
  • Hengl, T.、Miller, M.A.E.、Križan, J. 等人。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

使用 Earth Engine 探索

程式碼編輯器 (JavaScript)

var mean_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0-7" opacity="1" quantity="7"/>' +
  '<ColorMapEntry color="#002D6C" label="7-9" opacity="1" quantity="9"/>' +
  '<ColorMapEntry color="#16396D" label="9-10" opacity="1" quantity="10"/>' +
  '<ColorMapEntry color="#36476B" label="10-11" opacity="1" quantity="11"/>' +
  '<ColorMapEntry color="#4B546C" label="11-12" opacity="1" quantity="12"/>' +
  '<ColorMapEntry color="#5C616E" label="12-13" opacity="1" quantity="13"/>' +
  '<ColorMapEntry color="#6C6E72" label="13-14" opacity="1" quantity="14"/>' +
  '<ColorMapEntry color="#7C7B78" label="14-15" opacity="1" quantity="15"/>' +
  '<ColorMapEntry color="#8E8A79" label="15-16" opacity="1" quantity="16"/>' +
  '<ColorMapEntry color="#A09877" label="16-17" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#B3A772" label="17-18" opacity="1" quantity="18"/>' +
  '<ColorMapEntry color="#C6B66B" label="18-19" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#DBC761" label="19-20" opacity="1" quantity="20"/>' +
  '<ColorMapEntry color="#F0D852" label="20-22" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#FFEA46" label="22-70" opacity="1" quantity="24"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var mean_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0-7" opacity="1" quantity="7"/>' +
  '<ColorMapEntry color="#002D6C" label="7-9" opacity="1" quantity="9"/>' +
  '<ColorMapEntry color="#16396D" label="9-10" opacity="1" quantity="10"/>' +
  '<ColorMapEntry color="#36476B" label="10-11" opacity="1" quantity="11"/>' +
  '<ColorMapEntry color="#4B546C" label="11-12" opacity="1" quantity="12"/>' +
  '<ColorMapEntry color="#5C616E" label="12-13" opacity="1" quantity="13"/>' +
  '<ColorMapEntry color="#6C6E72" label="13-14" opacity="1" quantity="14"/>' +
  '<ColorMapEntry color="#7C7B78" label="14-15" opacity="1" quantity="15"/>' +
  '<ColorMapEntry color="#8E8A79" label="15-16" opacity="1" quantity="16"/>' +
  '<ColorMapEntry color="#A09877" label="16-17" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#B3A772" label="17-18" opacity="1" quantity="18"/>' +
  '<ColorMapEntry color="#C6B66B" label="18-19" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#DBC761" label="19-20" opacity="1" quantity="20"/>' +
  '<ColorMapEntry color="#F0D852" label="20-22" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#FFEA46" label="22-70" opacity="1" quantity="24"/>' +
 '</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="4.19000000000005"/>' +
 '</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="4.19000000000005"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

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

var converted = raw.divide(10).exp().subtract(1);

var visualization = {min: 0, max: 15};

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

Map.addLayer(converted.select(0), visualization, "Silt content, mean, 0-20 cm");
在程式碼編輯器中開啟