iSDAsoil Bulk Density, <2mm Fraction

ISDASOIL/Africa/v1/bulk_density
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/bulk_density")
標記
africa isda soil
bulk-density

說明

土壤深度 0-20 公分和 20-50 公分處的容積密度 (小於 2 公釐的分數)、預測平均值和標準差。

像素值必須使用 x/100 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 g/cm^3 44 197 公尺

容積密度,小於 2 公釐的分數,預測平均值為 0 到 20 公分深度

mean_20_50 g/cm^3 44 196 公尺

容積密度,<2 公釐的比例,預測平均深度為 20 到 50 公分

stdev_0_20 g/cm^3 0 92 公尺

容積密度 (小於 2 公釐的比例),0 到 20 公分深度的標準差

stdev_20_50 g/cm^3 0 92 公尺

容積密度,<2 公釐的比例,20 到 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.、Kri&zcaron;an, 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="0.8-1.05" 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");
在程式碼編輯器中開啟