
- Ketersediaan Set Data
- 2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
- Penyedia Set Data
- iSDA
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Deskripsi
Kepadatan massal, fraksi <2 mm pada kedalaman tanah 0-20 cm dan 20-50 cm, rerata dan standar deviasi yang diprediksi.
Nilai piksel harus ditransformasikan kembali dengan x/100
.
Di area hutan lebat (umumnya di Afrika tengah), akurasi model rendah dan oleh karena itu artefak seperti banding (garis-garis) mungkin terlihat.
Prediksi properti tanah dibuat oleh Innovative Solutions for Decision Agriculture Ltd. (iSDA) pada ukuran piksel 30 m menggunakan machine learning yang dipadukan dengan data penginderaan jauh dan set pelatihan lebih dari 100.000 sampel tanah yang dianalisis.
Informasi selengkapnya dapat ditemukan di FAQ dan dokumentasi informasi teknis. Untuk mengirimkan masalah atau meminta dukungan, buka situs iSDAsoil.
Band
Ukuran Piksel
30 meter
Band
Nama | Unit | Min | Maks | Ukuran Piksel | Deskripsi |
---|---|---|---|---|---|
mean_0_20 |
g/cm^3 | 44 | 197 | meter | Kepadatan massal, fraksi <2 mm, rata-rata yang diprediksi pada kedalaman 0-20 cm |
mean_20_50 |
g/cm^3 | 44 | 196 | meter | Kerapatan massal, fraksi <2 mm, rata-rata yang diprediksi pada kedalaman 20-50 cm |
stdev_0_20 |
g/cm^3 | 0 | 92 | meter | Kepadatan massal, fraksi <2 mm, standar deviasi pada kedalaman 0-20 cm |
stdev_20_50 |
g/cm^3 | 0 | 92 | meter | Kepadatan massal, fraksi <2 mm, standar deviasi pada kedalaman 20-50 cm |
Persyaratan Penggunaan
Persyaratan Penggunaan
Kutipan
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
Menjelajahi dengan Earth Engine
Code Editor (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");