Conteúdo volumétrico de água a 10kPa, 33kPa e 1500kPa de sucção em 10^-3 cm^3/cm^3 (0, 1 v% ou 1 mm/m) em 6 profundidades padrão (0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm). As previsões foram derivadas usando uma abordagem de mapeamento digital do solo baseada em floresta aleatória quantílica, com base em uma compilação global de dados de perfil do solo e camadas ambientais.
Esse conjunto de dados inclui previsões para três níveis de sucção diferentes, fornecendo insights sobre a disponibilidade de água no solo.
O conjunto de dados é organizado em três recursos principais: /wv0010, /wv0033 e /wv1500. Cada um desses recursos contém bandas que representam propriedades do solo em diferentes profundidades e quantis. Os nomes das faixas seguem o padrão val_<depth>_<quantile>, em que depth representa um intervalo de profundidade do solo (por exemplo, 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm) e quantile representa uma medida estatística (por exemplo, média, Q0,05, Q0,5, Q0,95).
Ainda não incluímos o intervalo de incerteza. É possível calcular a incerteza com base na proporção entre o intervalo interquartil (largura do intervalo de previsão de 90%) e a mediana: (Q0,95-Q0,05)/Q0,50.
Mapeamento global da retenção volumétrica de água a 100, 330 e 15.000 cm de sucção usando o banco de dados WoSIS. Turek M.E., Poggio L., Batjes N.H., Armindo R.A., de Jong van Lier Q.,
de Sousa L., Heuvelink G.B.M. (2023)
International Soil and Water Conservation Research, 11 (2), pp. 225-239.
Conteúdo volumétrico de água com sucção de 10 kPa, 33 kPa e 1.500 kPa em 10^-3 cm^3/cm^3 (0,1 v% ou 1 mm/m) em seis profundidades padrão (0 a 5 cm, 5 a 15 cm, 15 a 30 cm, 30 a 60 cm, 60 a 100 cm e 100 a 200 cm). As previsões foram derivadas usando uma abordagem de mapeamento digital do solo baseada em floresta aleatória quantílica, com base em uma compilação global de dados de perfil do solo…
[null,null,[],[],[],null,["# SoilGrids250m 2.0 - Volumetric Water Content\n\nDataset Availability\n: 1905-04-01T00:00:00Z--2016-07-05T00:00:00Z\n\nDataset Provider\n:\n\n\n [ISRIC - World Soil Information](https://www.isric.org/explore/soilgrids)\n\nTags\n:\n[soil](/earth-engine/datasets/tags/soil) [soil-moisture](/earth-engine/datasets/tags/soil-moisture) [water](/earth-engine/datasets/tags/water) \n\n#### Description\n\nVolumetric Water Content at 10kPa, 33kPa, and 1500kPa suction in\n10\\^-3 cm\\^3/cm\\^3 (0.1 v% or 1 mm/m) at 6 standard depths (0-5cm, 5-15cm,\n15-30cm, 30-60cm, 60-100cm, 100-200cm). Predictions were derived using a\ndigital soil mapping approach based on Quantile Random Forest, drawing on a\nglobal compilation of soil profile data and environmental layers.\nThis dataset includes predictions for three different suction levels,\nproviding insights into soil water availability.\n\nThe dataset is organized into three main assets: `/wv0010`, `/wv0033`,\nand `/wv1500`. Each of these assets contains bands representing soil\nproperties at different depths and quantiles. The band names follow the\npattern `val_\u003cdepth\u003e_\u003cquantile\u003e`, where `depth` represents a soil depth\nrange (e.g., 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm) and\n`quantile` represents a statistical measure (e.g., mean, Q0.05, Q0.5,\nQ0.95).\n\nThe uncertainty band is not yet included. It is possible to calculate\nthe uncertainty from the ratio between the inter-quantile range\n(90% prediction interval width) and the median: (Q0.95-Q0.05)/Q0.50.\n\nDocumentation:\n\n- [Scientific Paper](https://www.sciencedirect.com/science/article/pii/S2095633922000636?via%3Dihub)\n\n### Bands\n\n\n**Pixel Size**\n\n250 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|-----------------------|-------------|------------|--------------------------------------------------|\n| `val_0_5cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (0-5cm depth) |\n| `val_0_5cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (0-5cm depth) |\n| `val_5_15cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (5-15cm depth) |\n| `val_5_15cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (5-15cm depth) |\n| `val_15_30cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (15-30cm depth) |\n| `val_15_30cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (15-30cm depth) |\n| `val_30_60cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (30-60cm depth) |\n| `val_30_60cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (30-60cm depth) |\n| `val_60_100cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (60-100cm depth) |\n| `val_60_100cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (60-100cm depth) |\n| `val_100_200cm_mean` | cm\\^3/cm\\^3 | meters | Mean Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_05` | cm\\^3/cm\\^3 | meters | Q0.05 Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_5` | cm\\^3/cm\\^3 | meters | Q0.5 Volumetric Water Content (100-200cm depth) |\n| `val_100_200cm_Q0_95` | cm\\^3/cm\\^3 | meters | Q0.95 Volumetric Water Content (100-200cm depth) |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- Global mapping of volumetric water retention at 100, 330 and 15000 cm\n suction using the WoSIS database\n Turek M.E., Poggio L., Batjes N.H., Armindo R.A., de Jong van Lier Q.,\n de Sousa L., Heuvelink G.B.M. (2023)\n International Soil and Water Conservation Research, 11 (2), pp. 225-239.\n\n### DOIs\n\n- \u003chttps://doi.org/10.1016/j.iswcr.2022.08.001\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('ISRIC/SoilGrids250m/v2_0/wv0010').select('val_0_5cm_Q0_95');\n\nMap.setCenter(-105.25, 52.5, 3);\n\nMap.addLayer(\n dataset, {\n min: -0.061,\n max: 0.636,\n palette: [\n '#440154', '#482878', '#3E4A89', '#31688E', '#26828E', '#1F9E89',\n '#35B779', '#6DCD59', '#B4DE2C', '#FDE725'\n ]\n },\n 'SoilGrids250m 10kPa Q0.95 0-5cm');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/ISRIC/ISRIC_SoilGrids250m_v2_0) \n[SoilGrids250m 2.0 - Volumetric Water Content](/earth-engine/datasets/catalog/ISRIC_SoilGrids250m_v2_0) \nVolumetric Water Content at 10kPa, 33kPa, and 1500kPa suction in 10\\^-3 cm\\^3/cm\\^3 (0.1 v% or 1 mm/m) at 6 standard depths (0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm). Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data ... \nISRIC/SoilGrids250m/v2_0, soil,soil-moisture,water \n1905-04-01T00:00:00Z/2016-07-05T00:00:00Z \n-56 -180 84 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.1016/j.iswcr.2022.08.001](https://doi.org/https://www.isric.org/explore/soilgrids)\n- [https://doi.org/10.1016/j.iswcr.2022.08.001](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/ISRIC_SoilGrids250m_v2_0)"]]
