
- 資料集可用性
- 2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
- 資料集來源
- iSDA
- 標記
說明
土壤深度 0-20 公分和 20-50 公分的可萃取鋅、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和技術資訊說明文件。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 |
ppm | 1 | 32 | 公尺 | 鋅 (可萃取),預測平均值 (深度 0 到 20 公分) |
mean_20_50 |
ppm | 0 | 31 | 公尺 | 鋅 (可萃取),預測平均值 (深度 20 至 50 公分) |
stdev_0_20 |
ppm | 0 | 11 | 公尺 | 鋅 (可萃取),0 到 20 公分深度的標準差 |
stdev_20_50 |
ppm | 0 | 10 | 公尺 | 鋅,可萃取,20 至 50 公分深度的標準差 |
使用條款
使用條款
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="#0D0887" label="0-0.6" opacity="1" quantity="5"/>' + '<ColorMapEntry color="#350498" label="0.6-0.8" opacity="1" quantity="6"/>' + '<ColorMapEntry color="#5402A3" label="0.8-1" opacity="1" quantity="7"/>' + '<ColorMapEntry color="#7000A8" label="1-1.2" opacity="1" quantity="8"/>' + '<ColorMapEntry color="#8B0AA5" label="1.2-1.5" opacity="1" quantity="9"/>' + '<ColorMapEntry color="#A31E9A" label="1.5-1.7" opacity="1" quantity="10"/>' + '<ColorMapEntry color="#B93289" label="1.7-2" opacity="1" quantity="11"/>' + '<ColorMapEntry color="#CC4678" label="2-2.3" opacity="1" quantity="12"/>' + '<ColorMapEntry color="#DB5C68" label="2.3-2.7" opacity="1" quantity="13"/>' + '<ColorMapEntry color="#E97158" label="2.7-3.1" opacity="1" quantity="14"/>' + '<ColorMapEntry color="#F48849" label="3.1-3.5" opacity="1" quantity="15"/>' + '<ColorMapEntry color="#FBA139" label="3.5-4" opacity="1" quantity="16"/>' + '<ColorMapEntry color="#FEBC2A" label="4-4.5" opacity="1" quantity="17"/>' + '<ColorMapEntry color="#FADA24" label="4.5-5" opacity="1" quantity="18"/>' + '<ColorMapEntry color="#F0F921" label="5-125" opacity="1" quantity="19"/>' + '</ColorMap>' + '<ContrastEnhancement/>' + '</RasterSymbolizer>'; var mean_20_50 = '<RasterSymbolizer>' + '<ColorMap type="ramp">' + '<ColorMapEntry color="#0D0887" label="0-0.6" opacity="1" quantity="5"/>' + '<ColorMapEntry color="#350498" label="0.6-0.8" opacity="1" quantity="6"/>' + '<ColorMapEntry color="#5402A3" label="0.8-1" opacity="1" quantity="7"/>' + '<ColorMapEntry color="#7000A8" label="1-1.2" opacity="1" quantity="8"/>' + '<ColorMapEntry color="#8B0AA5" label="1.2-1.5" opacity="1" quantity="9"/>' + '<ColorMapEntry color="#A31E9A" label="1.5-1.7" opacity="1" quantity="10"/>' + '<ColorMapEntry color="#B93289" label="1.7-2" opacity="1" quantity="11"/>' + '<ColorMapEntry color="#CC4678" label="2-2.3" opacity="1" quantity="12"/>' + '<ColorMapEntry color="#DB5C68" label="2.3-2.7" opacity="1" quantity="13"/>' + '<ColorMapEntry color="#E97158" label="2.7-3.1" opacity="1" quantity="14"/>' + '<ColorMapEntry color="#F48849" label="3.1-3.5" opacity="1" quantity="15"/>' + '<ColorMapEntry color="#FBA139" label="3.5-4" opacity="1" quantity="16"/>' + '<ColorMapEntry color="#FEBC2A" label="4-4.5" opacity="1" quantity="17"/>' + '<ColorMapEntry color="#FADA24" label="4.5-5" opacity="1" quantity="18"/>' + '<ColorMapEntry color="#F0F921" label="5-125" opacity="1" quantity="19"/>' + '</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/zinc_extractable"); Map.addLayer( raw.select(0).sldStyle(mean_0_20), {}, "Zinc, extractable, mean visualization, 0-20 cm"); Map.addLayer( raw.select(1).sldStyle(mean_20_50), {}, "Zinc, extractable, mean visualization, 20-50 cm"); Map.addLayer( raw.select(2).sldStyle(stdev_0_20), {}, "Zinc, extractable, stdev visualization, 0-20 cm"); Map.addLayer( raw.select(3).sldStyle(stdev_20_50), {}, "Zinc, extractable, stdev visualization, 20-50 cm"); var converted = raw.divide(10).exp().subtract(1); var visualization = {min: 0, max: 10}; Map.setCenter(25, -3, 2); Map.addLayer(converted.select(0), visualization, "Zinc, extractable, mean, 0-20 cm");