iSDAsoil Clay Content

ISDASOIL/Africa/v1/clay_content
Disponibilidade de conjuntos de dados
2001-01-01T00:00:00Z–2017-01-01T00:00:00Z
Provedor de conjunto de dados
Snippet do Earth Engine
ee.Image("ISDASOIL/Africa/v1/clay_content")
Tags
africa clay isda soil

Descrição

Conteúdo de argila em profundidades de 0 a 20 cm e 20 a 50 cm, média e desvio padrão previstos. Em áreas de selva densa (geralmente na África Central), a acurácia do modelo é baixa e, portanto, podem aparecer artefatos como bandas (listras).

As previsões de propriedades do solo foram feitas pela Innovative Solutions for Decision Agriculture Ltd. (iSDA) com tamanho de pixel de 30 m usando machine learning e dados de sensoriamento remoto,além de um conjunto de treinamento de mais de 100.000 amostras de solo analisadas.

Mais informações podem ser encontradas no FAQ e na documentação de informações técnicas. Para enviar um problema ou pedir suporte, acesse o site do iSDAsoil.

Bandas

Tamanho do pixel
30 metros

Bandas

Nome Unidades Mín. Máx. Tamanho do pixel Descrição
mean_0_20 % 0 84 metros

Conteúdo de argila, média prevista em profundidade de 0 a 20 cm

mean_20_50 % 0 78 metros

Conteúdo de argila, média prevista em profundidade de 20 a 50 cm

stdev_0_20 % 0 90 metros

Conteúdo de argila, desvio padrão na profundidade de 0 a 20 cm

stdev_20_50 % 0 90 metros

Conteúdo de argila, desvio padrão na profundidade de 20 a 50 cm

Termos de Uso

Termos de Uso

CC-BY-4.0

Citações

Citações:
  • 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

Explorar com o Earth Engine

Editor de código (JavaScript)

var mean_0_20 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0-8" opacity="1" quantity="8"/>' +
  '<ColorMapEntry color="#002D6C" label="8-14" opacity="1" quantity="14"/>' +
  '<ColorMapEntry color="#16396D" label="14-17" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#36476B" label="17-19" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#4B546C" label="19-21" opacity="1" quantity="21"/>' +
  '<ColorMapEntry color="#5C616E" label="21-22" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#6C6E72" label="22-24" opacity="1" quantity="24"/>' +
  '<ColorMapEntry color="#7C7B78" label="24-25" opacity="1" quantity="25"/>' +
  '<ColorMapEntry color="#8E8A79" label="25-26" opacity="1" quantity="26"/>' +
  '<ColorMapEntry color="#A09877" label="26-28" opacity="1" quantity="28"/>' +
  '<ColorMapEntry color="#B3A772" label="28-30" opacity="1" quantity="30"/>' +
  '<ColorMapEntry color="#C6B66B" label="30-31" opacity="1" quantity="31"/>' +
  '<ColorMapEntry color="#DBC761" label="31-33" opacity="1" quantity="33"/>' +
  '<ColorMapEntry color="#F0D852" label="33-36" opacity="1" quantity="36"/>' +
  '<ColorMapEntry color="#FFEA46" label="36-70" opacity="1" quantity="40"/>' +
 '</ColorMap>' +
 '<ContrastEnhancement/>' +
'</RasterSymbolizer>';

var mean_20_50 =
'<RasterSymbolizer>' +
 '<ColorMap type="ramp">' +
  '<ColorMapEntry color="#00204D" label="0-8" opacity="1" quantity="8"/>' +
  '<ColorMapEntry color="#002D6C" label="8-14" opacity="1" quantity="14"/>' +
  '<ColorMapEntry color="#16396D" label="14-17" opacity="1" quantity="17"/>' +
  '<ColorMapEntry color="#36476B" label="17-19" opacity="1" quantity="19"/>' +
  '<ColorMapEntry color="#4B546C" label="19-21" opacity="1" quantity="21"/>' +
  '<ColorMapEntry color="#5C616E" label="21-22" opacity="1" quantity="22"/>' +
  '<ColorMapEntry color="#6C6E72" label="22-24" opacity="1" quantity="24"/>' +
  '<ColorMapEntry color="#7C7B78" label="24-25" opacity="1" quantity="25"/>' +
  '<ColorMapEntry color="#8E8A79" label="25-26" opacity="1" quantity="26"/>' +
  '<ColorMapEntry color="#A09877" label="26-28" opacity="1" quantity="28"/>' +
  '<ColorMapEntry color="#B3A772" label="28-30" opacity="1" quantity="30"/>' +
  '<ColorMapEntry color="#C6B66B" label="30-31" opacity="1" quantity="31"/>' +
  '<ColorMapEntry color="#DBC761" label="31-33" opacity="1" quantity="33"/>' +
  '<ColorMapEntry color="#F0D852" label="33-36" opacity="1" quantity="36"/>' +
  '<ColorMapEntry color="#FFEA46" label="36-70" opacity="1" quantity="40"/>' +
 '</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/clay_content");
Map.addLayer(
    raw.select(0).sldStyle(mean_0_20), {},
    "Clay content, mean visualization, 0-20 cm");
Map.addLayer(
    raw.select(1).sldStyle(mean_20_50), {},
    "Clay content, mean visualization, 20-50 cm");
Map.addLayer(
    raw.select(2).sldStyle(stdev_0_20), {},
    "Clay content, stdev visualization, 0-20 cm");
Map.addLayer(
    raw.select(3).sldStyle(stdev_20_50), {},
    "Clay content, stdev visualization, 20-50 cm");

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

var visualization = {min: 0, max: 50};

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

Map.addLayer(converted.select(0), visualization, "Clay content, mean, 0-20 cm");
Abrir no Editor de código